Instructions to use eaddario/Llama-Guard-3-8B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use eaddario/Llama-Guard-3-8B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="eaddario/Llama-Guard-3-8B-GGUF",
	filename="Llama-Guard-3-8B-F16.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use eaddario/Llama-Guard-3-8B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf eaddario/Llama-Guard-3-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf eaddario/Llama-Guard-3-8B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf eaddario/Llama-Guard-3-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf eaddario/Llama-Guard-3-8B-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf eaddario/Llama-Guard-3-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf eaddario/Llama-Guard-3-8B-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf eaddario/Llama-Guard-3-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf eaddario/Llama-Guard-3-8B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/eaddario/Llama-Guard-3-8B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use eaddario/Llama-Guard-3-8B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "eaddario/Llama-Guard-3-8B-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "eaddario/Llama-Guard-3-8B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/eaddario/Llama-Guard-3-8B-GGUF:Q4_K_M

Ollama
How to use eaddario/Llama-Guard-3-8B-GGUF with Ollama:
```
ollama run hf.co/eaddario/Llama-Guard-3-8B-GGUF:Q4_K_M
```

Unsloth Studio

How to use eaddario/Llama-Guard-3-8B-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for eaddario/Llama-Guard-3-8B-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for eaddario/Llama-Guard-3-8B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for eaddario/Llama-Guard-3-8B-GGUF to start chatting

Docker Model Runner
How to use eaddario/Llama-Guard-3-8B-GGUF with Docker Model Runner:
```
docker model run hf.co/eaddario/Llama-Guard-3-8B-GGUF:Q4_K_M
```

Lemonade

How to use eaddario/Llama-Guard-3-8B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull eaddario/Llama-Guard-3-8B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Llama-Guard-3-8B-GGUF-Q4_K_M

List all available models

lemonade list

eaddario commited on Apr 25, 2025

Commit

e517181

verified ·

1 Parent(s): cc1032a

Add GGUF internal file structure

Browse files

Files changed (13) hide show

scores/Llama-Guard-3-8B-F16.md +974 -0
scores/Llama-Guard-3-8B-IQ3_M.md +978 -0
scores/Llama-Guard-3-8B-IQ3_S.md +978 -0
scores/Llama-Guard-3-8B-IQ4_NL.md +978 -0
scores/Llama-Guard-3-8B-Q3_K_L.md +978 -0
scores/Llama-Guard-3-8B-Q3_K_M.md +978 -0
scores/Llama-Guard-3-8B-Q3_K_S.md +978 -0
scores/Llama-Guard-3-8B-Q4_K_M.md +978 -0
scores/Llama-Guard-3-8B-Q4_K_S.md +978 -0
scores/Llama-Guard-3-8B-Q5_K_M.md +978 -0
scores/Llama-Guard-3-8B-Q5_K_S.md +978 -0
scores/Llama-Guard-3-8B-Q6_K.md +978 -0
scores/Llama-Guard-3-8B-Q8_0.md +978 -0

scores/Llama-Guard-3-8B-F16.md ADDED Viewed

	@@ -0,0 +1,974 @@

+# Llama-Guard-3-8B-F16.gguf - GGUF Internal File Dump
+- Endian: LITTLE endian
+## Key Value Metadata Store
+There are 35 key-value pairs in this file
+| POS | TYPE     |  Count | Key                                    | Value                                                               |
+|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
+|   1 | UINT32   |      1 | GGUF.version                           | 3                                                                   |
+|   2 | UINT64   |      1 | GGUF.tensor_count                      | 292                                                                 |
+|   3 | UINT64   |      1 | GGUF.kv_count                          | 32                                                                  |
+|   4 | STRING   |      1 | general.architecture                   | `llama`                                                             |
+|   5 | STRING   |      1 | general.type                           | `model`                                                             |
+|   6 | STRING   |      1 | general.name                           | `Llama Guard 3 8B`                                                  |
+|   7 | STRING   |      1 | general.basename                       | `Llama-Guard-3`                                                     |
+|   8 | STRING   |      1 | general.size_label                     | `8B`                                                                |
+|   9 | STRING   |      1 | general.license                        | `llama3.1`                                                          |
+|  10 | UINT32   |      1 | general.base_model.count               | 1                                                                   |
+|  11 | STRING   |      1 | general.base_model.0.name              | `Meta Llama 3.1 8B`                                                 |
+|  12 | STRING   |      1 | general.base_model.0.organization      | `Meta Llama`                                                        |
+|  13 | STRING   |      1 | general.base_model.0.repo_url          | `https://huggingface.co/meta-llama/Meta-Llama-3.1-8B`               |
+|  14 | [STRING] |      6 | general.tags                           | [ `facebook`, `meta`, `pytorch`, `llama`, `llama-3`, ... ]          |
+|  15 | [STRING] |      1 | general.languages                      | [ `en` ]                                                            |
+|  16 | UINT32   |      1 | llama.block_count                      | 32                                                                  |
+|  17 | UINT32   |      1 | llama.context_length                   | 131072                                                              |
+|  18 | UINT32   |      1 | llama.embedding_length                 | 4096                                                                |
+|  19 | UINT32   |      1 | llama.feed_forward_length              | 14336                                                               |
+|  20 | UINT32   |      1 | llama.attention.head_count             | 32                                                                  |
+|  21 | UINT32   |      1 | llama.attention.head_count_kv          | 8                                                                   |
+|  22 | FLOAT32  |      1 | llama.rope.freq_base                   | 500000.0                                                            |
+|  23 | FLOAT32  |      1 | llama.attention.layer_norm_rms_epsilon | 1e-05                                                               |
+|  24 | UINT32   |      1 | general.file_type                      | 1                                                                   |
+|  25 | UINT32   |      1 | llama.vocab_size                       | 128256                                                              |
+|  26 | UINT32   |      1 | llama.rope.dimension_count             | 128                                                                 |
+|  27 | STRING   |      1 | tokenizer.ggml.model                   | `gpt2`                                                              |
+|  28 | STRING   |      1 | tokenizer.ggml.pre                     | `smaug-bpe`                                                         |
+|  29 | [STRING] | 128256 | tokenizer.ggml.tokens                  | [ `!`, `"`, `#`, `$`, `%`, ... ]                                    |
+|  30 | [INT32]  | 128256 | tokenizer.ggml.token_type              | [ 1, 1, 1, 1, 1, 1, 1, ... ]                                        |
+|  31 | [STRING] | 280147 | tokenizer.ggml.merges                  | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]                    |
+|  32 | UINT32   |      1 | tokenizer.ggml.bos_token_id            | 128000                                                              |
+|  33 | UINT32   |      1 | tokenizer.ggml.eos_token_id            | 128009                                                              |
+|  34 | STRING   |      1 | tokenizer.chat_template                | `{% if messages|length % 2 == 0`...`assistant<|end_header_id|>" }}` |
+|  35 | UINT32   |      1 | general.quantization_version           | 2                                                                   |
+## Tensors Overview ~8B Elements
+Total number of elements in all tensors: 8030261312 Elements
+- [Llama-Guard-3-8B-F16.gguf - GGUF Internal File Dump](#llama-guard-3-8b-f16gguf---gguf-internal-file-dump)
+  - [Key Value Metadata Store](#key-value-metadata-store)
+  - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
+    - [Tensor Data Offset](#tensor-data-offset)
+    - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
+    - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
+    - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
+    - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
+    - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
+    - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
+    - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
+    - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
+    - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
+    - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
+    - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
+    - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
+    - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
+    - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
+    - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
+    - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
+    - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
+    - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
+    - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
+    - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
+    - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
+    - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
+    - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
+    - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
+    - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
+    - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
+    - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
+    - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
+    - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
+    - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
+    - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
+    - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
+    - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
+### Tensor Data Offset
+This table contains the offset and data segment relative to start of file
+| T_ID | Tensor Layer Name         |  Data Offset (B) |    Data Size (B) |
+|-----:|:--------------------------|-----------------:|-----------------:|
+|    0 | rope_freqs.weight         |         0x779780 |            0x100 |
+|    1 | token_embd.weight         |         0x779880 |       0x3ea00000 |
+|    2 | blk.0.attn_norm.weight    |       0x3f179880 |           0x4000 |
+|    3 | blk.0.ffn_down.weight     |       0x3f17d880 |        0x7000000 |
+|    4 | blk.0.ffn_gate.weight     |       0x4617d880 |        0x7000000 |
+|    5 | blk.0.ffn_up.weight       |       0x4d17d880 |        0x7000000 |
+|    6 | blk.0.ffn_norm.weight     |       0x5417d880 |           0x4000 |
+|    7 | blk.0.attn_k.weight       |       0x54181880 |         0x800000 |
+|    8 | blk.0.attn_output.weight  |       0x54981880 |        0x2000000 |
+|    9 | blk.0.attn_q.weight       |       0x56981880 |        0x2000000 |
+|   10 | blk.0.attn_v.weight       |       0x58981880 |         0x800000 |
+|   11 | blk.1.attn_norm.weight    |       0x59181880 |           0x4000 |
+|   12 | blk.1.ffn_down.weight     |       0x59185880 |        0x7000000 |
+|   13 | blk.1.ffn_gate.weight     |       0x60185880 |        0x7000000 |
+|   14 | blk.1.ffn_up.weight       |       0x67185880 |        0x7000000 |
+|   15 | blk.1.ffn_norm.weight     |       0x6e185880 |           0x4000 |
+|   16 | blk.1.attn_k.weight       |       0x6e189880 |         0x800000 |
+|   17 | blk.1.attn_output.weight  |       0x6e989880 |        0x2000000 |
+|   18 | blk.1.attn_q.weight       |       0x70989880 |        0x2000000 |
+|   19 | blk.1.attn_v.weight       |       0x72989880 |         0x800000 |
+|   20 | blk.2.attn_norm.weight    |       0x73189880 |           0x4000 |
+|   21 | blk.2.ffn_down.weight     |       0x7318d880 |        0x7000000 |
+|   22 | blk.2.ffn_gate.weight     |       0x7a18d880 |        0x7000000 |
+|   23 | blk.2.ffn_up.weight       |       0x8118d880 |        0x7000000 |
+|   24 | blk.2.ffn_norm.weight     |       0x8818d880 |           0x4000 |
+|   25 | blk.2.attn_k.weight       |       0x88191880 |         0x800000 |
+|   26 | blk.2.attn_output.weight  |       0x88991880 |        0x2000000 |
+|   27 | blk.2.attn_q.weight       |       0x8a991880 |        0x2000000 |
+|   28 | blk.2.attn_v.weight       |       0x8c991880 |         0x800000 |
+|   29 | blk.3.attn_norm.weight    |       0x8d191880 |           0x4000 |
+|   30 | blk.3.ffn_down.weight     |       0x8d195880 |        0x7000000 |
+|   31 | blk.3.ffn_gate.weight     |       0x94195880 |        0x7000000 |
+|   32 | blk.3.ffn_up.weight       |       0x9b195880 |        0x7000000 |
+|   33 | blk.3.ffn_norm.weight     |       0xa2195880 |           0x4000 |
+|   34 | blk.3.attn_k.weight       |       0xa2199880 |         0x800000 |
+|   35 | blk.3.attn_output.weight  |       0xa2999880 |        0x2000000 |
+|   36 | blk.3.attn_q.weight       |       0xa4999880 |        0x2000000 |
+|   37 | blk.3.attn_v.weight       |       0xa6999880 |         0x800000 |
+|   38 | blk.4.attn_norm.weight    |       0xa7199880 |           0x4000 |
+|   39 | blk.4.ffn_down.weight     |       0xa719d880 |        0x7000000 |
+|   40 | blk.4.ffn_gate.weight     |       0xae19d880 |        0x7000000 |
+|   41 | blk.4.ffn_up.weight       |       0xb519d880 |        0x7000000 |
+|   42 | blk.4.ffn_norm.weight     |       0xbc19d880 |           0x4000 |
+|   43 | blk.4.attn_k.weight       |       0xbc1a1880 |         0x800000 |
+|   44 | blk.4.attn_output.weight  |       0xbc9a1880 |        0x2000000 |
+|   45 | blk.4.attn_q.weight       |       0xbe9a1880 |        0x2000000 |
+|   46 | blk.4.attn_v.weight       |       0xc09a1880 |         0x800000 |
+|   47 | blk.5.attn_norm.weight    |       0xc11a1880 |           0x4000 |
+|   48 | blk.5.ffn_down.weight     |       0xc11a5880 |        0x7000000 |
+|   49 | blk.5.ffn_gate.weight     |       0xc81a5880 |        0x7000000 |
+|   50 | blk.5.ffn_up.weight       |       0xcf1a5880 |        0x7000000 |
+|   51 | blk.5.ffn_norm.weight     |       0xd61a5880 |           0x4000 |
+|   52 | blk.5.attn_k.weight       |       0xd61a9880 |         0x800000 |
+|   53 | blk.5.attn_output.weight  |       0xd69a9880 |        0x2000000 |
+|   54 | blk.5.attn_q.weight       |       0xd89a9880 |        0x2000000 |
+|   55 | blk.5.attn_v.weight       |       0xda9a9880 |         0x800000 |
+|   56 | blk.6.attn_norm.weight    |       0xdb1a9880 |           0x4000 |
+|   57 | blk.6.ffn_down.weight     |       0xdb1ad880 |        0x7000000 |
+|   58 | blk.6.ffn_gate.weight     |       0xe21ad880 |        0x7000000 |
+|   59 | blk.6.ffn_up.weight       |       0xe91ad880 |        0x7000000 |
+|   60 | blk.6.ffn_norm.weight     |       0xf01ad880 |           0x4000 |
+|   61 | blk.6.attn_k.weight       |       0xf01b1880 |         0x800000 |
+|   62 | blk.6.attn_output.weight  |       0xf09b1880 |        0x2000000 |
+|   63 | blk.6.attn_q.weight       |       0xf29b1880 |        0x2000000 |
+|   64 | blk.6.attn_v.weight       |       0xf49b1880 |         0x800000 |
+|   65 | blk.7.attn_norm.weight    |       0xf51b1880 |           0x4000 |
+|   66 | blk.7.ffn_down.weight     |       0xf51b5880 |        0x7000000 |
+|   67 | blk.7.ffn_gate.weight     |       0xfc1b5880 |        0x7000000 |
+|   68 | blk.7.ffn_up.weight       |      0x1031b5880 |        0x7000000 |
+|   69 | blk.7.ffn_norm.weight     |      0x10a1b5880 |           0x4000 |
+|   70 | blk.7.attn_k.weight       |      0x10a1b9880 |         0x800000 |
+|   71 | blk.7.attn_output.weight  |      0x10a9b9880 |        0x2000000 |
+|   72 | blk.7.attn_q.weight       |      0x10c9b9880 |        0x2000000 |
+|   73 | blk.7.attn_v.weight       |      0x10e9b9880 |         0x800000 |
+|   74 | blk.8.attn_norm.weight    |      0x10f1b9880 |           0x4000 |
+|   75 | blk.8.ffn_down.weight     |      0x10f1bd880 |        0x7000000 |
+|   76 | blk.8.ffn_gate.weight     |      0x1161bd880 |        0x7000000 |
+|   77 | blk.8.ffn_up.weight       |      0x11d1bd880 |        0x7000000 |
+|   78 | blk.8.ffn_norm.weight     |      0x1241bd880 |           0x4000 |
+|   79 | blk.8.attn_k.weight       |      0x1241c1880 |         0x800000 |
+|   80 | blk.8.attn_output.weight  |      0x1249c1880 |        0x2000000 |
+|   81 | blk.8.attn_q.weight       |      0x1269c1880 |        0x2000000 |
+|   82 | blk.8.attn_v.weight       |      0x1289c1880 |         0x800000 |
+|   83 | blk.10.attn_norm.weight   |      0x1291c1880 |           0x4000 |
+|   84 | blk.10.ffn_down.weight    |      0x1291c5880 |        0x7000000 |
+|   85 | blk.10.ffn_gate.weight    |      0x1301c5880 |        0x7000000 |
+|   86 | blk.10.ffn_up.weight      |      0x1371c5880 |        0x7000000 |
+|   87 | blk.10.ffn_norm.weight    |      0x13e1c5880 |           0x4000 |
+|   88 | blk.10.attn_k.weight      |      0x13e1c9880 |         0x800000 |
+|   89 | blk.10.attn_output.weight |      0x13e9c9880 |        0x2000000 |
+|   90 | blk.10.attn_q.weight      |      0x1409c9880 |        0x2000000 |
+|   91 | blk.10.attn_v.weight      |      0x1429c9880 |         0x800000 |
+|   92 | blk.11.attn_norm.weight   |      0x1431c9880 |           0x4000 |
+|   93 | blk.11.ffn_down.weight    |      0x1431cd880 |        0x7000000 |
+|   94 | blk.11.ffn_gate.weight    |      0x14a1cd880 |        0x7000000 |
+|   95 | blk.11.ffn_up.weight      |      0x1511cd880 |        0x7000000 |
+|   96 | blk.11.ffn_norm.weight    |      0x1581cd880 |           0x4000 |
+|   97 | blk.11.attn_k.weight      |      0x1581d1880 |         0x800000 |
+|   98 | blk.11.attn_output.weight |      0x1589d1880 |        0x2000000 |
+|   99 | blk.11.attn_q.weight      |      0x15a9d1880 |        0x2000000 |
+|  100 | blk.11.attn_v.weight      |      0x15c9d1880 |         0x800000 |
+|  101 | blk.12.attn_norm.weight   |      0x15d1d1880 |           0x4000 |
+|  102 | blk.12.ffn_down.weight    |      0x15d1d5880 |        0x7000000 |
+|  103 | blk.12.ffn_gate.weight    |      0x1641d5880 |        0x7000000 |
+|  104 | blk.12.ffn_up.weight      |      0x16b1d5880 |        0x7000000 |
+|  105 | blk.12.ffn_norm.weight    |      0x1721d5880 |           0x4000 |
+|  106 | blk.12.attn_k.weight      |      0x1721d9880 |         0x800000 |
+|  107 | blk.12.attn_output.weight |      0x1729d9880 |        0x2000000 |
+|  108 | blk.12.attn_q.weight      |      0x1749d9880 |        0x2000000 |
+|  109 | blk.12.attn_v.weight      |      0x1769d9880 |         0x800000 |
+|  110 | blk.13.attn_norm.weight   |      0x1771d9880 |           0x4000 |
+|  111 | blk.13.ffn_down.weight    |      0x1771dd880 |        0x7000000 |
+|  112 | blk.13.ffn_gate.weight    |      0x17e1dd880 |        0x7000000 |
+|  113 | blk.13.ffn_up.weight      |      0x1851dd880 |        0x7000000 |
+|  114 | blk.13.ffn_norm.weight    |      0x18c1dd880 |           0x4000 |
+|  115 | blk.13.attn_k.weight      |      0x18c1e1880 |         0x800000 |
+|  116 | blk.13.attn_output.weight |      0x18c9e1880 |        0x2000000 |
+|  117 | blk.13.attn_q.weight      |      0x18e9e1880 |        0x2000000 |
+|  118 | blk.13.attn_v.weight      |      0x1909e1880 |         0x800000 |
+|  119 | blk.14.attn_norm.weight   |      0x1911e1880 |           0x4000 |
+|  120 | blk.14.ffn_down.weight    |      0x1911e5880 |        0x7000000 |
+|  121 | blk.14.ffn_gate.weight    |      0x1981e5880 |        0x7000000 |
+|  122 | blk.14.ffn_up.weight      |      0x19f1e5880 |        0x7000000 |
+|  123 | blk.14.ffn_norm.weight    |      0x1a61e5880 |           0x4000 |
+|  124 | blk.14.attn_k.weight      |      0x1a61e9880 |         0x800000 |
+|  125 | blk.14.attn_output.weight |      0x1a69e9880 |        0x2000000 |
+|  126 | blk.14.attn_q.weight      |      0x1a89e9880 |        0x2000000 |
+|  127 | blk.14.attn_v.weight      |      0x1aa9e9880 |         0x800000 |
+|  128 | blk.15.attn_norm.weight   |      0x1ab1e9880 |           0x4000 |
+|  129 | blk.15.ffn_down.weight    |      0x1ab1ed880 |        0x7000000 |
+|  130 | blk.15.ffn_gate.weight    |      0x1b21ed880 |        0x7000000 |
+|  131 | blk.15.ffn_up.weight      |      0x1b91ed880 |        0x7000000 |
+|  132 | blk.15.ffn_norm.weight    |      0x1c01ed880 |           0x4000 |
+|  133 | blk.15.attn_k.weight      |      0x1c01f1880 |         0x800000 |
+|  134 | blk.15.attn_output.weight |      0x1c09f1880 |        0x2000000 |
+|  135 | blk.15.attn_q.weight      |      0x1c29f1880 |        0x2000000 |
+|  136 | blk.15.attn_v.weight      |      0x1c49f1880 |         0x800000 |
+|  137 | blk.16.attn_norm.weight   |      0x1c51f1880 |           0x4000 |
+|  138 | blk.16.ffn_down.weight    |      0x1c51f5880 |        0x7000000 |
+|  139 | blk.16.ffn_gate.weight    |      0x1cc1f5880 |        0x7000000 |
+|  140 | blk.16.ffn_up.weight      |      0x1d31f5880 |        0x7000000 |
+|  141 | blk.16.ffn_norm.weight    |      0x1da1f5880 |           0x4000 |
+|  142 | blk.16.attn_k.weight      |      0x1da1f9880 |         0x800000 |
+|  143 | blk.16.attn_output.weight |      0x1da9f9880 |        0x2000000 |
+|  144 | blk.16.attn_q.weight      |      0x1dc9f9880 |        0x2000000 |
+|  145 | blk.16.attn_v.weight      |      0x1de9f9880 |         0x800000 |
+|  146 | blk.17.attn_norm.weight   |      0x1df1f9880 |           0x4000 |
+|  147 | blk.17.ffn_down.weight    |      0x1df1fd880 |        0x7000000 |
+|  148 | blk.17.ffn_gate.weight    |      0x1e61fd880 |        0x7000000 |
+|  149 | blk.17.ffn_up.weight      |      0x1ed1fd880 |        0x7000000 |
+|  150 | blk.17.ffn_norm.weight    |      0x1f41fd880 |           0x4000 |
+|  151 | blk.17.attn_k.weight      |      0x1f4201880 |         0x800000 |
+|  152 | blk.17.attn_output.weight |      0x1f4a01880 |        0x2000000 |
+|  153 | blk.17.attn_q.weight      |      0x1f6a01880 |        0x2000000 |
+|  154 | blk.17.attn_v.weight      |      0x1f8a01880 |         0x800000 |
+|  155 | blk.18.attn_norm.weight   |      0x1f9201880 |           0x4000 |
+|  156 | blk.18.ffn_down.weight    |      0x1f9205880 |        0x7000000 |
+|  157 | blk.18.ffn_gate.weight    |      0x200205880 |        0x7000000 |
+|  158 | blk.18.ffn_up.weight      |      0x207205880 |        0x7000000 |
+|  159 | blk.18.ffn_norm.weight    |      0x20e205880 |           0x4000 |
+|  160 | blk.18.attn_k.weight      |      0x20e209880 |         0x800000 |
+|  161 | blk.18.attn_output.weight |      0x20ea09880 |        0x2000000 |
+|  162 | blk.18.attn_q.weight      |      0x210a09880 |        0x2000000 |
+|  163 | blk.18.attn_v.weight      |      0x212a09880 |         0x800000 |
+|  164 | blk.19.attn_norm.weight   |      0x213209880 |           0x4000 |
+|  165 | blk.19.ffn_down.weight    |      0x21320d880 |        0x7000000 |
+|  166 | blk.19.ffn_gate.weight    |      0x21a20d880 |        0x7000000 |
+|  167 | blk.19.ffn_up.weight      |      0x22120d880 |        0x7000000 |
+|  168 | blk.19.ffn_norm.weight    |      0x22820d880 |           0x4000 |
+|  169 | blk.19.attn_k.weight      |      0x228211880 |         0x800000 |
+|  170 | blk.19.attn_output.weight |      0x228a11880 |        0x2000000 |
+|  171 | blk.19.attn_q.weight      |      0x22aa11880 |        0x2000000 |
+|  172 | blk.19.attn_v.weight      |      0x22ca11880 |         0x800000 |
+|  173 | blk.20.ffn_gate.weight    |      0x22d211880 |        0x7000000 |
+|  174 | blk.20.attn_k.weight      |      0x234211880 |         0x800000 |
+|  175 | blk.20.attn_output.weight |      0x234a11880 |        0x2000000 |
+|  176 | blk.20.attn_q.weight      |      0x236a11880 |        0x2000000 |
+|  177 | blk.20.attn_v.weight      |      0x238a11880 |         0x800000 |
+|  178 | blk.9.attn_norm.weight    |      0x239211880 |           0x4000 |
+|  179 | blk.9.ffn_down.weight     |      0x239215880 |        0x7000000 |
+|  180 | blk.9.ffn_gate.weight     |      0x240215880 |        0x7000000 |
+|  181 | blk.9.ffn_up.weight       |      0x247215880 |        0x7000000 |
+|  182 | blk.9.ffn_norm.weight     |      0x24e215880 |           0x4000 |
+|  183 | blk.9.attn_k.weight       |      0x24e219880 |         0x800000 |
+|  184 | blk.9.attn_output.weight  |      0x24ea19880 |        0x2000000 |
+|  185 | blk.9.attn_q.weight       |      0x250a19880 |        0x2000000 |
+|  186 | blk.9.attn_v.weight       |      0x252a19880 |         0x800000 |
+|  187 | blk.20.attn_norm.weight   |      0x253219880 |           0x4000 |
+|  188 | blk.20.ffn_down.weight    |      0x25321d880 |        0x7000000 |
+|  189 | blk.20.ffn_up.weight      |      0x25a21d880 |        0x7000000 |
+|  190 | blk.20.ffn_norm.weight    |      0x26121d880 |           0x4000 |
+|  191 | blk.21.attn_norm.weight   |      0x261221880 |           0x4000 |
+|  192 | blk.21.ffn_down.weight    |      0x261225880 |        0x7000000 |
+|  193 | blk.21.ffn_gate.weight    |      0x268225880 |        0x7000000 |
+|  194 | blk.21.ffn_up.weight      |      0x26f225880 |        0x7000000 |
+|  195 | blk.21.ffn_norm.weight    |      0x276225880 |           0x4000 |
+|  196 | blk.21.attn_k.weight      |      0x276229880 |         0x800000 |
+|  197 | blk.21.attn_output.weight |      0x276a29880 |        0x2000000 |
+|  198 | blk.21.attn_q.weight      |      0x278a29880 |        0x2000000 |
+|  199 | blk.21.attn_v.weight      |      0x27aa29880 |         0x800000 |
+|  200 | blk.22.attn_norm.weight   |      0x27b229880 |           0x4000 |
+|  201 | blk.22.ffn_down.weight    |      0x27b22d880 |        0x7000000 |
+|  202 | blk.22.ffn_gate.weight    |      0x28222d880 |        0x7000000 |
+|  203 | blk.22.ffn_up.weight      |      0x28922d880 |        0x7000000 |
+|  204 | blk.22.ffn_norm.weight    |      0x29022d880 |           0x4000 |
+|  205 | blk.22.attn_k.weight      |      0x290231880 |         0x800000 |
+|  206 | blk.22.attn_output.weight |      0x290a31880 |        0x2000000 |
+|  207 | blk.22.attn_q.weight      |      0x292a31880 |        0x2000000 |
+|  208 | blk.22.attn_v.weight      |      0x294a31880 |         0x800000 |
+|  209 | blk.23.attn_norm.weight   |      0x295231880 |           0x4000 |
+|  210 | blk.23.ffn_down.weight    |      0x295235880 |        0x7000000 |
+|  211 | blk.23.ffn_gate.weight    |      0x29c235880 |        0x7000000 |
+|  212 | blk.23.ffn_up.weight      |      0x2a3235880 |        0x7000000 |
+|  213 | blk.23.ffn_norm.weight    |      0x2aa235880 |           0x4000 |
+|  214 | blk.23.attn_k.weight      |      0x2aa239880 |         0x800000 |
+|  215 | blk.23.attn_output.weight |      0x2aaa39880 |        0x2000000 |
+|  216 | blk.23.attn_q.weight      |      0x2aca39880 |        0x2000000 |
+|  217 | blk.23.attn_v.weight      |      0x2aea39880 |         0x800000 |
+|  218 | blk.24.attn_norm.weight   |      0x2af239880 |           0x4000 |
+|  219 | blk.24.ffn_down.weight    |      0x2af23d880 |        0x7000000 |
+|  220 | blk.24.ffn_gate.weight    |      0x2b623d880 |        0x7000000 |
+|  221 | blk.24.ffn_up.weight      |      0x2bd23d880 |        0x7000000 |
+|  222 | blk.24.ffn_norm.weight    |      0x2c423d880 |           0x4000 |
+|  223 | blk.24.attn_k.weight      |      0x2c4241880 |         0x800000 |
+|  224 | blk.24.attn_output.weight |      0x2c4a41880 |        0x2000000 |
+|  225 | blk.24.attn_q.weight      |      0x2c6a41880 |        0x2000000 |
+|  226 | blk.24.attn_v.weight      |      0x2c8a41880 |         0x800000 |
+|  227 | blk.25.attn_norm.weight   |      0x2c9241880 |           0x4000 |
+|  228 | blk.25.ffn_down.weight    |      0x2c9245880 |        0x7000000 |
+|  229 | blk.25.ffn_gate.weight    |      0x2d0245880 |        0x7000000 |
+|  230 | blk.25.ffn_up.weight      |      0x2d7245880 |        0x7000000 |
+|  231 | blk.25.ffn_norm.weight    |      0x2de245880 |           0x4000 |
+|  232 | blk.25.attn_k.weight      |      0x2de249880 |         0x800000 |
+|  233 | blk.25.attn_output.weight |      0x2dea49880 |        0x2000000 |
+|  234 | blk.25.attn_q.weight      |      0x2e0a49880 |        0x2000000 |
+|  235 | blk.25.attn_v.weight      |      0x2e2a49880 |         0x800000 |
+|  236 | blk.26.attn_norm.weight   |      0x2e3249880 |           0x4000 |
+|  237 | blk.26.ffn_down.weight    |      0x2e324d880 |        0x7000000 |
+|  238 | blk.26.ffn_gate.weight    |      0x2ea24d880 |        0x7000000 |
+|  239 | blk.26.ffn_up.weight      |      0x2f124d880 |        0x7000000 |
+|  240 | blk.26.ffn_norm.weight    |      0x2f824d880 |           0x4000 |
+|  241 | blk.26.attn_k.weight      |      0x2f8251880 |         0x800000 |
+|  242 | blk.26.attn_output.weight |      0x2f8a51880 |        0x2000000 |
+|  243 | blk.26.attn_q.weight      |      0x2faa51880 |        0x2000000 |
+|  244 | blk.26.attn_v.weight      |      0x2fca51880 |         0x800000 |
+|  245 | blk.27.attn_norm.weight   |      0x2fd251880 |           0x4000 |
+|  246 | blk.27.ffn_down.weight    |      0x2fd255880 |        0x7000000 |
+|  247 | blk.27.ffn_gate.weight    |      0x304255880 |        0x7000000 |
+|  248 | blk.27.ffn_up.weight      |      0x30b255880 |        0x7000000 |
+|  249 | blk.27.ffn_norm.weight    |      0x312255880 |           0x4000 |
+|  250 | blk.27.attn_k.weight      |      0x312259880 |         0x800000 |
+|  251 | blk.27.attn_output.weight |      0x312a59880 |        0x2000000 |
+|  252 | blk.27.attn_q.weight      |      0x314a59880 |        0x2000000 |
+|  253 | blk.27.attn_v.weight      |      0x316a59880 |         0x800000 |
+|  254 | blk.28.attn_norm.weight   |      0x317259880 |           0x4000 |
+|  255 | blk.28.ffn_down.weight    |      0x31725d880 |        0x7000000 |
+|  256 | blk.28.ffn_gate.weight    |      0x31e25d880 |        0x7000000 |
+|  257 | blk.28.ffn_up.weight      |      0x32525d880 |        0x7000000 |
+|  258 | blk.28.ffn_norm.weight    |      0x32c25d880 |           0x4000 |
+|  259 | blk.28.attn_k.weight      |      0x32c261880 |         0x800000 |
+|  260 | blk.28.attn_output.weight |      0x32ca61880 |        0x2000000 |
+|  261 | blk.28.attn_q.weight      |      0x32ea61880 |        0x2000000 |
+|  262 | blk.28.attn_v.weight      |      0x330a61880 |         0x800000 |
+|  263 | blk.29.attn_norm.weight   |      0x331261880 |           0x4000 |
+|  264 | blk.29.ffn_down.weight    |      0x331265880 |        0x7000000 |
+|  265 | blk.29.ffn_gate.weight    |      0x338265880 |        0x7000000 |
+|  266 | blk.29.ffn_up.weight      |      0x33f265880 |        0x7000000 |
+|  267 | blk.29.ffn_norm.weight    |      0x346265880 |           0x4000 |
+|  268 | blk.29.attn_k.weight      |      0x346269880 |         0x800000 |
+|  269 | blk.29.attn_output.weight |      0x346a69880 |        0x2000000 |
+|  270 | blk.29.attn_q.weight      |      0x348a69880 |        0x2000000 |
+|  271 | blk.29.attn_v.weight      |      0x34aa69880 |         0x800000 |
+|  272 | blk.30.attn_norm.weight   |      0x34b269880 |           0x4000 |
+|  273 | blk.30.ffn_down.weight    |      0x34b26d880 |        0x7000000 |
+|  274 | blk.30.ffn_gate.weight    |      0x35226d880 |        0x7000000 |
+|  275 | blk.30.ffn_up.weight      |      0x35926d880 |        0x7000000 |
+|  276 | blk.30.ffn_norm.weight    |      0x36026d880 |           0x4000 |
+|  277 | blk.30.attn_k.weight      |      0x360271880 |         0x800000 |
+|  278 | blk.30.attn_output.weight |      0x360a71880 |        0x2000000 |
+|  279 | blk.30.attn_q.weight      |      0x362a71880 |        0x2000000 |
+|  280 | blk.30.attn_v.weight      |      0x364a71880 |         0x800000 |
+|  281 | blk.31.ffn_gate.weight    |      0x365271880 |        0x7000000 |
+|  282 | blk.31.ffn_up.weight      |      0x36c271880 |        0x7000000 |
+|  283 | blk.31.attn_k.weight      |      0x373271880 |         0x800000 |
+|  284 | blk.31.attn_output.weight |      0x373a71880 |        0x2000000 |
+|  285 | blk.31.attn_q.weight      |      0x375a71880 |        0x2000000 |
+|  286 | blk.31.attn_v.weight      |      0x377a71880 |         0x800000 |
+|  287 | output.weight             |      0x378271880 |       0x3ea00000 |
+|  288 | blk.31.attn_norm.weight   |      0x3b6c71880 |           0x4000 |
+|  289 | blk.31.ffn_down.weight    |      0x3b6c75880 |        0x7000000 |
+|  290 | blk.31.ffn_norm.weight    |      0x3bdc75880 |           0x4000 |
+|  291 | output_norm.weight        |      0x3bdc79880 |           0x4000 |
+### <a name="base">Base Tensor Group : ~1B Elements</a>
+| T_ID | Tensor Layer Name  | Human Friendly Tensor Layer Name | Elements          | Shape                 | Type |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
+|    0 | rope_freqs.weight  | Rope_Freqs (W)                   | (   64)        64 |   64 x      1 x 1 x 1 | F32  |
+|    1 | token_embd.weight  | Token Embedding (W)              | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | F16  |
+|  287 | output.weight      | Output (W)                       | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | F16  |
+|  291 | output_norm.weight | Output Normalization (W)         | (  ~4K)      4096 | 4096 x      1 x 1 x 1 | F32  |
+- Total elements in base: ( ~1B) 1050677312
+- Percentage of total elements: 13.08%
+### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|    2 | blk.0.attn_norm.weight   | Block 0 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|    3 | blk.0.ffn_down.weight    | Block 0 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|    4 | blk.0.ffn_gate.weight    | Block 0 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|    5 | blk.0.ffn_up.weight      | Block 0 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|    6 | blk.0.ffn_norm.weight    | Block 0 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|    7 | blk.0.attn_k.weight      | Block 0 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|    8 | blk.0.attn_output.weight | Block 0 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|    9 | blk.0.attn_q.weight      | Block 0 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   10 | blk.0.attn_v.weight      | Block 0 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.0: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   11 | blk.1.attn_norm.weight   | Block 1 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   12 | blk.1.ffn_down.weight    | Block 1 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|   13 | blk.1.ffn_gate.weight    | Block 1 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   14 | blk.1.ffn_up.weight      | Block 1 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   15 | blk.1.ffn_norm.weight    | Block 1 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   16 | blk.1.attn_k.weight      | Block 1 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|   17 | blk.1.attn_output.weight | Block 1 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   18 | blk.1.attn_q.weight      | Block 1 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   19 | blk.1.attn_v.weight      | Block 1 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.1: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   20 | blk.2.attn_norm.weight   | Block 2 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   21 | blk.2.ffn_down.weight    | Block 2 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|   22 | blk.2.ffn_gate.weight    | Block 2 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   23 | blk.2.ffn_up.weight      | Block 2 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   24 | blk.2.ffn_norm.weight    | Block 2 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   25 | blk.2.attn_k.weight      | Block 2 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|   26 | blk.2.attn_output.weight | Block 2 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   27 | blk.2.attn_q.weight      | Block 2 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   28 | blk.2.attn_v.weight      | Block 2 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.2: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   29 | blk.3.attn_norm.weight   | Block 3 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   30 | blk.3.ffn_down.weight    | Block 3 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|   31 | blk.3.ffn_gate.weight    | Block 3 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   32 | blk.3.ffn_up.weight      | Block 3 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   33 | blk.3.ffn_norm.weight    | Block 3 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   34 | blk.3.attn_k.weight      | Block 3 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|   35 | blk.3.attn_output.weight | Block 3 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   36 | blk.3.attn_q.weight      | Block 3 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   37 | blk.3.attn_v.weight      | Block 3 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.3: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   38 | blk.4.attn_norm.weight   | Block 4 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   39 | blk.4.ffn_down.weight    | Block 4 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|   40 | blk.4.ffn_gate.weight    | Block 4 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   41 | blk.4.ffn_up.weight      | Block 4 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   42 | blk.4.ffn_norm.weight    | Block 4 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   43 | blk.4.attn_k.weight      | Block 4 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|   44 | blk.4.attn_output.weight | Block 4 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   45 | blk.4.attn_q.weight      | Block 4 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   46 | blk.4.attn_v.weight      | Block 4 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.4: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   47 | blk.5.attn_norm.weight   | Block 5 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   48 | blk.5.ffn_down.weight    | Block 5 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|   49 | blk.5.ffn_gate.weight    | Block 5 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   50 | blk.5.ffn_up.weight      | Block 5 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   51 | blk.5.ffn_norm.weight    | Block 5 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   52 | blk.5.attn_k.weight      | Block 5 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|   53 | blk.5.attn_output.weight | Block 5 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   54 | blk.5.attn_q.weight      | Block 5 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   55 | blk.5.attn_v.weight      | Block 5 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.5: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   56 | blk.6.attn_norm.weight   | Block 6 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   57 | blk.6.ffn_down.weight    | Block 6 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|   58 | blk.6.ffn_gate.weight    | Block 6 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   59 | blk.6.ffn_up.weight      | Block 6 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   60 | blk.6.ffn_norm.weight    | Block 6 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   61 | blk.6.attn_k.weight      | Block 6 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|   62 | blk.6.attn_output.weight | Block 6 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   63 | blk.6.attn_q.weight      | Block 6 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   64 | blk.6.attn_v.weight      | Block 6 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.6: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   65 | blk.7.attn_norm.weight   | Block 7 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   66 | blk.7.ffn_down.weight    | Block 7 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|   67 | blk.7.ffn_gate.weight    | Block 7 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   68 | blk.7.ffn_up.weight      | Block 7 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   69 | blk.7.ffn_norm.weight    | Block 7 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   70 | blk.7.attn_k.weight      | Block 7 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|   71 | blk.7.attn_output.weight | Block 7 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   72 | blk.7.attn_q.weight      | Block 7 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   73 | blk.7.attn_v.weight      | Block 7 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.7: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   74 | blk.8.attn_norm.weight   | Block 8 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   75 | blk.8.ffn_down.weight    | Block 8 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|   76 | blk.8.ffn_gate.weight    | Block 8 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   77 | blk.8.ffn_up.weight      | Block 8 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   78 | blk.8.ffn_norm.weight    | Block 8 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   79 | blk.8.attn_k.weight      | Block 8 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|   80 | blk.8.attn_output.weight | Block 8 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   81 | blk.8.attn_q.weight      | Block 8 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   82 | blk.8.attn_v.weight      | Block 8 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.8: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|   83 | blk.10.attn_norm.weight   | Block 10 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   84 | blk.10.ffn_down.weight    | Block 10 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|   85 | blk.10.ffn_gate.weight    | Block 10 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   86 | blk.10.ffn_up.weight      | Block 10 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   87 | blk.10.ffn_norm.weight    | Block 10 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   88 | blk.10.attn_k.weight      | Block 10 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|   89 | blk.10.attn_output.weight | Block 10 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   90 | blk.10.attn_q.weight      | Block 10 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   91 | blk.10.attn_v.weight      | Block 10 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.10: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|   92 | blk.11.attn_norm.weight   | Block 11 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   93 | blk.11.ffn_down.weight    | Block 11 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|   94 | blk.11.ffn_gate.weight    | Block 11 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   95 | blk.11.ffn_up.weight      | Block 11 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|   96 | blk.11.ffn_norm.weight    | Block 11 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   97 | blk.11.attn_k.weight      | Block 11 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|   98 | blk.11.attn_output.weight | Block 11 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|   99 | blk.11.attn_q.weight      | Block 11 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  100 | blk.11.attn_v.weight      | Block 11 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.11: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  101 | blk.12.attn_norm.weight   | Block 12 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  102 | blk.12.ffn_down.weight    | Block 12 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  103 | blk.12.ffn_gate.weight    | Block 12 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  104 | blk.12.ffn_up.weight      | Block 12 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  105 | blk.12.ffn_norm.weight    | Block 12 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  106 | blk.12.attn_k.weight      | Block 12 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  107 | blk.12.attn_output.weight | Block 12 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  108 | blk.12.attn_q.weight      | Block 12 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  109 | blk.12.attn_v.weight      | Block 12 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.12: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  110 | blk.13.attn_norm.weight   | Block 13 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  111 | blk.13.ffn_down.weight    | Block 13 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  112 | blk.13.ffn_gate.weight    | Block 13 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  113 | blk.13.ffn_up.weight      | Block 13 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  114 | blk.13.ffn_norm.weight    | Block 13 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  115 | blk.13.attn_k.weight      | Block 13 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  116 | blk.13.attn_output.weight | Block 13 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  117 | blk.13.attn_q.weight      | Block 13 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  118 | blk.13.attn_v.weight      | Block 13 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.13: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  119 | blk.14.attn_norm.weight   | Block 14 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  120 | blk.14.ffn_down.weight    | Block 14 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  121 | blk.14.ffn_gate.weight    | Block 14 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  122 | blk.14.ffn_up.weight      | Block 14 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  123 | blk.14.ffn_norm.weight    | Block 14 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  124 | blk.14.attn_k.weight      | Block 14 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  125 | blk.14.attn_output.weight | Block 14 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  126 | blk.14.attn_q.weight      | Block 14 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  127 | blk.14.attn_v.weight      | Block 14 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.14: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  128 | blk.15.attn_norm.weight   | Block 15 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  129 | blk.15.ffn_down.weight    | Block 15 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  130 | blk.15.ffn_gate.weight    | Block 15 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  131 | blk.15.ffn_up.weight      | Block 15 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  132 | blk.15.ffn_norm.weight    | Block 15 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  133 | blk.15.attn_k.weight      | Block 15 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  134 | blk.15.attn_output.weight | Block 15 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  135 | blk.15.attn_q.weight      | Block 15 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  136 | blk.15.attn_v.weight      | Block 15 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.15: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  137 | blk.16.attn_norm.weight   | Block 16 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  138 | blk.16.ffn_down.weight    | Block 16 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  139 | blk.16.ffn_gate.weight    | Block 16 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  140 | blk.16.ffn_up.weight      | Block 16 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  141 | blk.16.ffn_norm.weight    | Block 16 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  142 | blk.16.attn_k.weight      | Block 16 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  143 | blk.16.attn_output.weight | Block 16 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  144 | blk.16.attn_q.weight      | Block 16 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  145 | blk.16.attn_v.weight      | Block 16 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.16: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  146 | blk.17.attn_norm.weight   | Block 17 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  147 | blk.17.ffn_down.weight    | Block 17 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  148 | blk.17.ffn_gate.weight    | Block 17 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  149 | blk.17.ffn_up.weight      | Block 17 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  150 | blk.17.ffn_norm.weight    | Block 17 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  151 | blk.17.attn_k.weight      | Block 17 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  152 | blk.17.attn_output.weight | Block 17 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  153 | blk.17.attn_q.weight      | Block 17 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  154 | blk.17.attn_v.weight      | Block 17 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.17: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  155 | blk.18.attn_norm.weight   | Block 18 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  156 | blk.18.ffn_down.weight    | Block 18 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  157 | blk.18.ffn_gate.weight    | Block 18 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  158 | blk.18.ffn_up.weight      | Block 18 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  159 | blk.18.ffn_norm.weight    | Block 18 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  160 | blk.18.attn_k.weight      | Block 18 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  161 | blk.18.attn_output.weight | Block 18 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  162 | blk.18.attn_q.weight      | Block 18 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  163 | blk.18.attn_v.weight      | Block 18 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.18: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  164 | blk.19.attn_norm.weight   | Block 19 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  165 | blk.19.ffn_down.weight    | Block 19 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  166 | blk.19.ffn_gate.weight    | Block 19 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  167 | blk.19.ffn_up.weight      | Block 19 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  168 | blk.19.ffn_norm.weight    | Block 19 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  169 | blk.19.attn_k.weight      | Block 19 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  170 | blk.19.attn_output.weight | Block 19 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  171 | blk.19.attn_q.weight      | Block 19 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  172 | blk.19.attn_v.weight      | Block 19 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.19: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  173 | blk.20.ffn_gate.weight    | Block 20 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  174 | blk.20.attn_k.weight      | Block 20 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  175 | blk.20.attn_output.weight | Block 20 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  176 | blk.20.attn_q.weight      | Block 20 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  177 | blk.20.attn_v.weight      | Block 20 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  187 | blk.20.attn_norm.weight   | Block 20 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  188 | blk.20.ffn_down.weight    | Block 20 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  189 | blk.20.ffn_up.weight      | Block 20 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  190 | blk.20.ffn_norm.weight    | Block 20 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+- Total elements in blk.20: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|  178 | blk.9.attn_norm.weight   | Block 9 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  179 | blk.9.ffn_down.weight    | Block 9 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  180 | blk.9.ffn_gate.weight    | Block 9 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  181 | blk.9.ffn_up.weight      | Block 9 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  182 | blk.9.ffn_norm.weight    | Block 9 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  183 | blk.9.attn_k.weight      | Block 9 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  184 | blk.9.attn_output.weight | Block 9 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  185 | blk.9.attn_q.weight      | Block 9 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  186 | blk.9.attn_v.weight      | Block 9 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.9: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  191 | blk.21.attn_norm.weight   | Block 21 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  192 | blk.21.ffn_down.weight    | Block 21 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  193 | blk.21.ffn_gate.weight    | Block 21 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  194 | blk.21.ffn_up.weight      | Block 21 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  195 | blk.21.ffn_norm.weight    | Block 21 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  196 | blk.21.attn_k.weight      | Block 21 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  197 | blk.21.attn_output.weight | Block 21 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  198 | blk.21.attn_q.weight      | Block 21 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  199 | blk.21.attn_v.weight      | Block 21 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.21: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  200 | blk.22.attn_norm.weight   | Block 22 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  201 | blk.22.ffn_down.weight    | Block 22 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  202 | blk.22.ffn_gate.weight    | Block 22 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  203 | blk.22.ffn_up.weight      | Block 22 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  204 | blk.22.ffn_norm.weight    | Block 22 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  205 | blk.22.attn_k.weight      | Block 22 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  206 | blk.22.attn_output.weight | Block 22 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  207 | blk.22.attn_q.weight      | Block 22 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  208 | blk.22.attn_v.weight      | Block 22 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.22: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  209 | blk.23.attn_norm.weight   | Block 23 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  210 | blk.23.ffn_down.weight    | Block 23 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  211 | blk.23.ffn_gate.weight    | Block 23 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  212 | blk.23.ffn_up.weight      | Block 23 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  213 | blk.23.ffn_norm.weight    | Block 23 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  214 | blk.23.attn_k.weight      | Block 23 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  215 | blk.23.attn_output.weight | Block 23 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  216 | blk.23.attn_q.weight      | Block 23 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  217 | blk.23.attn_v.weight      | Block 23 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.23: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  218 | blk.24.attn_norm.weight   | Block 24 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  219 | blk.24.ffn_down.weight    | Block 24 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  220 | blk.24.ffn_gate.weight    | Block 24 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  221 | blk.24.ffn_up.weight      | Block 24 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  222 | blk.24.ffn_norm.weight    | Block 24 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  223 | blk.24.attn_k.weight      | Block 24 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  224 | blk.24.attn_output.weight | Block 24 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  225 | blk.24.attn_q.weight      | Block 24 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  226 | blk.24.attn_v.weight      | Block 24 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.24: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  227 | blk.25.attn_norm.weight   | Block 25 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  228 | blk.25.ffn_down.weight    | Block 25 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  229 | blk.25.ffn_gate.weight    | Block 25 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  230 | blk.25.ffn_up.weight      | Block 25 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  231 | blk.25.ffn_norm.weight    | Block 25 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  232 | blk.25.attn_k.weight      | Block 25 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  233 | blk.25.attn_output.weight | Block 25 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  234 | blk.25.attn_q.weight      | Block 25 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  235 | blk.25.attn_v.weight      | Block 25 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.25: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  236 | blk.26.attn_norm.weight   | Block 26 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  237 | blk.26.ffn_down.weight    | Block 26 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  238 | blk.26.ffn_gate.weight    | Block 26 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  239 | blk.26.ffn_up.weight      | Block 26 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  240 | blk.26.ffn_norm.weight    | Block 26 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  241 | blk.26.attn_k.weight      | Block 26 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  242 | blk.26.attn_output.weight | Block 26 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  243 | blk.26.attn_q.weight      | Block 26 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  244 | blk.26.attn_v.weight      | Block 26 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.26: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  245 | blk.27.attn_norm.weight   | Block 27 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  246 | blk.27.ffn_down.weight    | Block 27 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  247 | blk.27.ffn_gate.weight    | Block 27 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  248 | blk.27.ffn_up.weight      | Block 27 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  249 | blk.27.ffn_norm.weight    | Block 27 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  250 | blk.27.attn_k.weight      | Block 27 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  251 | blk.27.attn_output.weight | Block 27 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  252 | blk.27.attn_q.weight      | Block 27 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  253 | blk.27.attn_v.weight      | Block 27 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.27: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  254 | blk.28.attn_norm.weight   | Block 28 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  255 | blk.28.ffn_down.weight    | Block 28 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  256 | blk.28.ffn_gate.weight    | Block 28 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  257 | blk.28.ffn_up.weight      | Block 28 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  258 | blk.28.ffn_norm.weight    | Block 28 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  259 | blk.28.attn_k.weight      | Block 28 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  260 | blk.28.attn_output.weight | Block 28 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  261 | blk.28.attn_q.weight      | Block 28 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  262 | blk.28.attn_v.weight      | Block 28 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.28: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  263 | blk.29.attn_norm.weight   | Block 29 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  264 | blk.29.ffn_down.weight    | Block 29 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  265 | blk.29.ffn_gate.weight    | Block 29 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  266 | blk.29.ffn_up.weight      | Block 29 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  267 | blk.29.ffn_norm.weight    | Block 29 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  268 | blk.29.attn_k.weight      | Block 29 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  269 | blk.29.attn_output.weight | Block 29 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  270 | blk.29.attn_q.weight      | Block 29 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  271 | blk.29.attn_v.weight      | Block 29 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.29: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  272 | blk.30.attn_norm.weight   | Block 30 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  273 | blk.30.ffn_down.weight    | Block 30 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  274 | blk.30.ffn_gate.weight    | Block 30 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  275 | blk.30.ffn_up.weight      | Block 30 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  276 | blk.30.ffn_norm.weight    | Block 30 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  277 | blk.30.attn_k.weight      | Block 30 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  278 | blk.30.attn_output.weight | Block 30 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  279 | blk.30.attn_q.weight      | Block 30 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  280 | blk.30.attn_v.weight      | Block 30 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+- Total elements in blk.30: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  281 | blk.31.ffn_gate.weight    | Block 31 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  282 | blk.31.ffn_up.weight      | Block 31 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | F16  |
+|  283 | blk.31.attn_k.weight      | Block 31 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  284 | blk.31.attn_output.weight | Block 31 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  285 | blk.31.attn_q.weight      | Block 31 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | F16  |
+|  286 | blk.31.attn_v.weight      | Block 31 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  288 | blk.31.attn_norm.weight   | Block 31 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  289 | blk.31.ffn_down.weight    | Block 31 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | F16  |
+|  290 | blk.31.ffn_norm.weight    | Block 31 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+- Total elements in blk.31: (~218M) 218112000
+- Percentage of total elements: 2.72%

scores/Llama-Guard-3-8B-IQ3_M.md ADDED Viewed

	@@ -0,0 +1,978 @@

+# Llama-Guard-3-8B-IQ3_M.gguf - GGUF Internal File Dump
+- Endian: LITTLE endian
+## Key Value Metadata Store
+There are 39 key-value pairs in this file
+| POS | TYPE     |  Count | Key                                    | Value                                                               |
+|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
+|   1 | UINT32   |      1 | GGUF.version                           | 3                                                                   |
+|   2 | UINT64   |      1 | GGUF.tensor_count                      | 292                                                                 |
+|   3 | UINT64   |      1 | GGUF.kv_count                          | 36                                                                  |
+|   4 | STRING   |      1 | general.architecture                   | `llama`                                                             |
+|   5 | STRING   |      1 | general.type                           | `model`                                                             |
+|   6 | STRING   |      1 | general.name                           | `Llama Guard 3 8B`                                                  |
+|   7 | STRING   |      1 | general.basename                       | `Llama-Guard-3`                                                     |
+|   8 | STRING   |      1 | general.size_label                     | `8B`                                                                |
+|   9 | STRING   |      1 | general.license                        | `llama3.1`                                                          |
+|  10 | UINT32   |      1 | general.base_model.count               | 1                                                                   |
+|  11 | STRING   |      1 | general.base_model.0.name              | `Meta Llama 3.1 8B`                                                 |
+|  12 | STRING   |      1 | general.base_model.0.organization      | `Meta Llama`                                                        |
+|  13 | STRING   |      1 | general.base_model.0.repo_url          | `https://huggingface.co/meta-llama/Meta-Llama-3.1-8B`               |
+|  14 | [STRING] |      6 | general.tags                           | [ `facebook`, `meta`, `pytorch`, `llama`, `llama-3`, ... ]          |
+|  15 | [STRING] |      1 | general.languages                      | [ `en` ]                                                            |
+|  16 | UINT32   |      1 | llama.block_count                      | 32                                                                  |
+|  17 | UINT32   |      1 | llama.context_length                   | 131072                                                              |
+|  18 | UINT32   |      1 | llama.embedding_length                 | 4096                                                                |
+|  19 | UINT32   |      1 | llama.feed_forward_length              | 14336                                                               |
+|  20 | UINT32   |      1 | llama.attention.head_count             | 32                                                                  |
+|  21 | UINT32   |      1 | llama.attention.head_count_kv          | 8                                                                   |
+|  22 | FLOAT32  |      1 | llama.rope.freq_base                   | 500000.0                                                            |
+|  23 | FLOAT32  |      1 | llama.attention.layer_norm_rms_epsilon | 1e-05                                                               |
+|  24 | UINT32   |      1 | llama.vocab_size                       | 128256                                                              |
+|  25 | UINT32   |      1 | llama.rope.dimension_count             | 128                                                                 |
+|  26 | STRING   |      1 | tokenizer.ggml.model                   | `gpt2`                                                              |
+|  27 | STRING   |      1 | tokenizer.ggml.pre                     | `smaug-bpe`                                                         |
+|  28 | [STRING] | 128256 | tokenizer.ggml.tokens                  | [ `!`, `"`, `#`, `$`, `%`, ... ]                                    |
+|  29 | [INT32]  | 128256 | tokenizer.ggml.token_type              | [ 1, 1, 1, 1, 1, 1, 1, ... ]                                        |
+|  30 | [STRING] | 280147 | tokenizer.ggml.merges                  | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]                    |
+|  31 | UINT32   |      1 | tokenizer.ggml.bos_token_id            | 128000                                                              |
+|  32 | UINT32   |      1 | tokenizer.ggml.eos_token_id            | 128009                                                              |
+|  33 | STRING   |      1 | tokenizer.chat_template                | `{% if messages|length % 2 == 0`...`assistant<|end_header_id|>" }}` |
+|  34 | UINT32   |      1 | general.quantization_version           | 2                                                                   |
+|  35 | UINT32   |      1 | general.file_type                      | 27                                                                  |
+|  36 | STRING   |      1 | quantize.imatrix.file                  | `./imatrix/imatrix-Llama-Guard-3-8B-small.dat`                      |
+|  37 | STRING   |      1 | quantize.imatrix.dataset               | `../../datasets/imatrix/calibration_eur_small.txt`                  |
+|  38 | INT32    |      1 | quantize.imatrix.entries_count         | 224                                                                 |
+|  39 | INT32    |      1 | quantize.imatrix.chunks_count          | 962                                                                 |
+## Tensors Overview ~8B Elements
+Total number of elements in all tensors: 8030261312 Elements
+- [Llama-Guard-3-8B-IQ3\_M.gguf - GGUF Internal File Dump](#llama-guard-3-8b-iq3_mgguf---gguf-internal-file-dump)
+  - [Key Value Metadata Store](#key-value-metadata-store)
+  - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
+    - [Tensor Data Offset](#tensor-data-offset)
+    - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
+    - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
+    - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
+    - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
+    - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
+    - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
+    - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
+    - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
+    - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
+    - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
+    - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
+    - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
+    - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
+    - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
+    - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
+    - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
+    - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
+    - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
+    - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
+    - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
+    - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
+    - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
+    - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
+    - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
+    - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
+    - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
+    - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
+    - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
+    - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
+    - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
+    - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
+    - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
+    - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
+### Tensor Data Offset
+This table contains the offset and data segment relative to start of file
+| T_ID | Tensor Layer Name         |  Data Offset (B) |    Data Size (B) |
+|-----:|:--------------------------|-----------------:|-----------------:|
+|    0 | output.weight             |         0x779880 |        0xd746000 |
+|    1 | output_norm.weight        |        0xdebf880 |           0x4000 |
+|    2 | rope_freqs.weight         |        0xdec3880 |            0x100 |
+|    3 | token_embd.weight         |        0xdec3980 |        0xd746000 |
+|    4 | blk.0.attn_k.weight       |       0x1b609980 |         0x188000 |
+|    5 | blk.0.attn_norm.weight    |       0x1b791980 |           0x4000 |
+|    6 | blk.0.attn_output.weight  |       0x1b795980 |         0x900000 |
+|    7 | blk.0.attn_q.weight       |       0x1c095980 |         0x620000 |
+|    8 | blk.0.attn_v.weight       |       0x1c6b5980 |         0x1b8000 |
+|    9 | blk.0.ffn_down.weight     |       0x1c86d980 |        0x1f80000 |
+|   10 | blk.0.ffn_gate.weight     |       0x1e7ed980 |        0x1570000 |
+|   11 | blk.0.ffn_norm.weight     |       0x1fd5d980 |           0x4000 |
+|   12 | blk.0.ffn_up.weight       |       0x1fd61980 |        0x1570000 |
+|   13 | blk.1.attn_k.weight       |       0x212d1980 |         0x188000 |
+|   14 | blk.1.attn_norm.weight    |       0x21459980 |           0x4000 |
+|   15 | blk.1.attn_output.weight  |       0x2145d980 |         0x900000 |
+|   16 | blk.1.attn_q.weight       |       0x21d5d980 |         0x620000 |
+|   17 | blk.1.attn_v.weight       |       0x2237d980 |         0x1b8000 |
+|   18 | blk.1.ffn_down.weight     |       0x22535980 |        0x1f80000 |
+|   19 | blk.1.ffn_gate.weight     |       0x244b5980 |        0x1570000 |
+|   20 | blk.1.ffn_norm.weight     |       0x25a25980 |           0x4000 |
+|   21 | blk.1.ffn_up.weight       |       0x25a29980 |        0x1570000 |
+|   22 | blk.2.attn_k.weight       |       0x26f99980 |         0x188000 |
+|   23 | blk.2.attn_norm.weight    |       0x27121980 |           0x4000 |
+|   24 | blk.2.attn_output.weight  |       0x27125980 |         0x900000 |
+|   25 | blk.2.attn_q.weight       |       0x27a25980 |         0x620000 |
+|   26 | blk.2.attn_v.weight       |       0x28045980 |         0x1b8000 |
+|   27 | blk.2.ffn_down.weight     |       0x281fd980 |        0x1f80000 |
+|   28 | blk.2.ffn_gate.weight     |       0x2a17d980 |        0x1570000 |
+|   29 | blk.2.ffn_norm.weight     |       0x2b6ed980 |           0x4000 |
+|   30 | blk.2.ffn_up.weight       |       0x2b6f1980 |        0x1570000 |
+|   31 | blk.3.attn_k.weight       |       0x2cc61980 |         0x188000 |
+|   32 | blk.3.attn_norm.weight    |       0x2cde9980 |           0x4000 |
+|   33 | blk.3.attn_output.weight  |       0x2cded980 |         0x900000 |
+|   34 | blk.3.attn_q.weight       |       0x2d6ed980 |         0x620000 |
+|   35 | blk.3.attn_v.weight       |       0x2dd0d980 |         0x1b8000 |
+|   36 | blk.3.ffn_down.weight     |       0x2dec5980 |        0x1f80000 |
+|   37 | blk.3.ffn_gate.weight     |       0x2fe45980 |        0x1570000 |
+|   38 | blk.3.ffn_norm.weight     |       0x313b5980 |           0x4000 |
+|   39 | blk.3.ffn_up.weight       |       0x313b9980 |        0x1570000 |
+|   40 | blk.4.attn_k.weight       |       0x32929980 |         0x188000 |
+|   41 | blk.4.attn_norm.weight    |       0x32ab1980 |           0x4000 |
+|   42 | blk.4.attn_output.weight  |       0x32ab5980 |         0x900000 |
+|   43 | blk.4.attn_q.weight       |       0x333b5980 |         0x620000 |
+|   44 | blk.4.attn_v.weight       |       0x339d5980 |         0x1b8000 |
+|   45 | blk.4.ffn_down.weight     |       0x33b8d980 |        0x1f80000 |
+|   46 | blk.4.ffn_gate.weight     |       0x35b0d980 |        0x1570000 |
+|   47 | blk.4.ffn_norm.weight     |       0x3707d980 |           0x4000 |
+|   48 | blk.4.ffn_up.weight       |       0x37081980 |        0x1570000 |
+|   49 | blk.5.attn_k.weight       |       0x385f1980 |         0x188000 |
+|   50 | blk.5.attn_norm.weight    |       0x38779980 |           0x4000 |
+|   51 | blk.5.attn_output.weight  |       0x3877d980 |         0x900000 |
+|   52 | blk.5.attn_q.weight       |       0x3907d980 |         0x620000 |
+|   53 | blk.5.attn_v.weight       |       0x3969d980 |         0x1b8000 |
+|   54 | blk.5.ffn_down.weight     |       0x39855980 |        0x1f80000 |
+|   55 | blk.5.ffn_gate.weight     |       0x3b7d5980 |        0x1570000 |
+|   56 | blk.5.ffn_norm.weight     |       0x3cd45980 |           0x4000 |
+|   57 | blk.5.ffn_up.weight       |       0x3cd49980 |        0x1570000 |
+|   58 | blk.6.attn_k.weight       |       0x3e2b9980 |         0x188000 |
+|   59 | blk.6.attn_norm.weight    |       0x3e441980 |           0x4000 |
+|   60 | blk.6.attn_output.weight  |       0x3e445980 |         0x900000 |
+|   61 | blk.6.attn_q.weight       |       0x3ed45980 |         0x620000 |
+|   62 | blk.6.attn_v.weight       |       0x3f365980 |         0x1b8000 |
+|   63 | blk.6.ffn_down.weight     |       0x3f51d980 |        0x1f80000 |
+|   64 | blk.6.ffn_gate.weight     |       0x4149d980 |        0x1570000 |
+|   65 | blk.6.ffn_norm.weight     |       0x42a0d980 |           0x4000 |
+|   66 | blk.6.ffn_up.weight       |       0x42a11980 |        0x1570000 |
+|   67 | blk.7.attn_k.weight       |       0x43f81980 |         0x188000 |
+|   68 | blk.7.attn_norm.weight    |       0x44109980 |           0x4000 |
+|   69 | blk.7.attn_output.weight  |       0x4410d980 |         0x900000 |
+|   70 | blk.7.attn_q.weight       |       0x44a0d980 |         0x620000 |
+|   71 | blk.7.attn_v.weight       |       0x4502d980 |         0x1b8000 |
+|   72 | blk.7.ffn_down.weight     |       0x451e5980 |        0x1f80000 |
+|   73 | blk.7.ffn_gate.weight     |       0x47165980 |        0x1570000 |
+|   74 | blk.7.ffn_norm.weight     |       0x486d5980 |           0x4000 |
+|   75 | blk.7.ffn_up.weight       |       0x486d9980 |        0x1570000 |
+|   76 | blk.8.attn_k.weight       |       0x49c49980 |         0x188000 |
+|   77 | blk.8.attn_norm.weight    |       0x49dd1980 |           0x4000 |
+|   78 | blk.8.attn_output.weight  |       0x49dd5980 |         0x900000 |
+|   79 | blk.8.attn_q.weight       |       0x4a6d5980 |         0x620000 |
+|   80 | blk.8.attn_v.weight       |       0x4acf5980 |         0x1b8000 |
+|   81 | blk.8.ffn_down.weight     |       0x4aead980 |        0x1f80000 |
+|   82 | blk.8.ffn_gate.weight     |       0x4ce2d980 |        0x1570000 |
+|   83 | blk.8.ffn_norm.weight     |       0x4e39d980 |           0x4000 |
+|   84 | blk.8.ffn_up.weight       |       0x4e3a1980 |        0x1570000 |
+|   85 | blk.9.attn_k.weight       |       0x4f911980 |         0x188000 |
+|   86 | blk.9.attn_norm.weight    |       0x4fa99980 |           0x4000 |
+|   87 | blk.9.attn_output.weight  |       0x4fa9d980 |         0x900000 |
+|   88 | blk.9.attn_q.weight       |       0x5039d980 |         0x620000 |
+|   89 | blk.9.attn_v.weight       |       0x509bd980 |         0x1b8000 |
+|   90 | blk.9.ffn_down.weight     |       0x50b75980 |        0x1f80000 |
+|   91 | blk.9.ffn_gate.weight     |       0x52af5980 |        0x1570000 |
+|   92 | blk.9.ffn_norm.weight     |       0x54065980 |           0x4000 |
+|   93 | blk.9.ffn_up.weight       |       0x54069980 |        0x1570000 |
+|   94 | blk.10.attn_k.weight      |       0x555d9980 |         0x188000 |
+|   95 | blk.10.attn_norm.weight   |       0x55761980 |           0x4000 |
+|   96 | blk.10.attn_output.weight |       0x55765980 |         0x900000 |
+|   97 | blk.10.attn_q.weight      |       0x56065980 |         0x620000 |
+|   98 | blk.10.attn_v.weight      |       0x56685980 |         0x1b8000 |
+|   99 | blk.10.ffn_down.weight    |       0x5683d980 |        0x1f80000 |
+|  100 | blk.10.ffn_gate.weight    |       0x587bd980 |        0x1570000 |
+|  101 | blk.10.ffn_norm.weight    |       0x59d2d980 |           0x4000 |
+|  102 | blk.10.ffn_up.weight      |       0x59d31980 |        0x1570000 |
+|  103 | blk.11.attn_k.weight      |       0x5b2a1980 |         0x188000 |
+|  104 | blk.11.attn_norm.weight   |       0x5b429980 |           0x4000 |
+|  105 | blk.11.attn_output.weight |       0x5b42d980 |         0x900000 |
+|  106 | blk.11.attn_q.weight      |       0x5bd2d980 |         0x620000 |
+|  107 | blk.11.attn_v.weight      |       0x5c34d980 |         0x1b8000 |
+|  108 | blk.11.ffn_down.weight    |       0x5c505980 |        0x1f80000 |
+|  109 | blk.11.ffn_gate.weight    |       0x5e485980 |        0x1570000 |
+|  110 | blk.11.ffn_norm.weight    |       0x5f9f5980 |           0x4000 |
+|  111 | blk.11.ffn_up.weight      |       0x5f9f9980 |        0x1570000 |
+|  112 | blk.12.attn_k.weight      |       0x60f69980 |         0x188000 |
+|  113 | blk.12.attn_norm.weight   |       0x610f1980 |           0x4000 |
+|  114 | blk.12.attn_output.weight |       0x610f5980 |         0x900000 |
+|  115 | blk.12.attn_q.weight      |       0x619f5980 |         0x620000 |
+|  116 | blk.12.attn_v.weight      |       0x62015980 |         0x1b8000 |
+|  117 | blk.12.ffn_down.weight    |       0x621cd980 |        0x1f80000 |
+|  118 | blk.12.ffn_gate.weight    |       0x6414d980 |        0x1570000 |
+|  119 | blk.12.ffn_norm.weight    |       0x656bd980 |           0x4000 |
+|  120 | blk.12.ffn_up.weight      |       0x656c1980 |        0x1570000 |
+|  121 | blk.13.attn_k.weight      |       0x66c31980 |         0x1b8000 |
+|  122 | blk.13.attn_norm.weight   |       0x66de9980 |           0x4000 |
+|  123 | blk.13.attn_output.weight |       0x66ded980 |         0x900000 |
+|  124 | blk.13.attn_q.weight      |       0x676ed980 |         0x6e0000 |
+|  125 | blk.13.attn_v.weight      |       0x67dcd980 |         0x240000 |
+|  126 | blk.13.ffn_down.weight    |       0x6800d980 |        0x1f80000 |
+|  127 | blk.13.ffn_gate.weight    |       0x69f8d980 |        0x1570000 |
+|  128 | blk.13.ffn_norm.weight    |       0x6b4fd980 |           0x4000 |
+|  129 | blk.13.ffn_up.weight      |       0x6b501980 |        0x1570000 |
+|  130 | blk.14.attn_k.weight      |       0x6ca71980 |         0x1b8000 |
+|  131 | blk.14.attn_norm.weight   |       0x6cc29980 |           0x4000 |
+|  132 | blk.14.attn_output.weight |       0x6cc2d980 |         0x900000 |
+|  133 | blk.14.attn_q.weight      |       0x6d52d980 |         0x6e0000 |
+|  134 | blk.14.attn_v.weight      |       0x6dc0d980 |         0x240000 |
+|  135 | blk.14.ffn_down.weight    |       0x6de4d980 |        0x1f80000 |
+|  136 | blk.14.ffn_gate.weight    |       0x6fdcd980 |        0x1570000 |
+|  137 | blk.14.ffn_norm.weight    |       0x7133d980 |           0x4000 |
+|  138 | blk.14.ffn_up.weight      |       0x71341980 |        0x1570000 |
+|  139 | blk.15.attn_k.weight      |       0x728b1980 |         0x188000 |
+|  140 | blk.15.attn_norm.weight   |       0x72a39980 |           0x4000 |
+|  141 | blk.15.attn_output.weight |       0x72a3d980 |         0x900000 |
+|  142 | blk.15.attn_q.weight      |       0x7333d980 |         0x620000 |
+|  143 | blk.15.attn_v.weight      |       0x7395d980 |         0x1b8000 |
+|  144 | blk.15.ffn_down.weight    |       0x73b15980 |        0x1f80000 |
+|  145 | blk.15.ffn_gate.weight    |       0x75a95980 |        0x1570000 |
+|  146 | blk.15.ffn_norm.weight    |       0x77005980 |           0x4000 |
+|  147 | blk.15.ffn_up.weight      |       0x77009980 |        0x1570000 |
+|  148 | blk.16.attn_k.weight      |       0x78579980 |         0x1b8000 |
+|  149 | blk.16.attn_norm.weight   |       0x78731980 |           0x4000 |
+|  150 | blk.16.attn_output.weight |       0x78735980 |         0x900000 |
+|  151 | blk.16.attn_q.weight      |       0x79035980 |         0x6e0000 |
+|  152 | blk.16.attn_v.weight      |       0x79715980 |         0x240000 |
+|  153 | blk.16.ffn_down.weight    |       0x79955980 |        0x1f80000 |
+|  154 | blk.16.ffn_gate.weight    |       0x7b8d5980 |        0x1810000 |
+|  155 | blk.16.ffn_norm.weight    |       0x7d0e5980 |           0x4000 |
+|  156 | blk.16.ffn_up.weight      |       0x7d0e9980 |        0x1810000 |
+|  157 | blk.17.attn_k.weight      |       0x7e8f9980 |         0x188000 |
+|  158 | blk.17.attn_norm.weight   |       0x7ea81980 |           0x4000 |
+|  159 | blk.17.attn_output.weight |       0x7ea85980 |         0x900000 |
+|  160 | blk.17.attn_q.weight      |       0x7f385980 |         0x620000 |
+|  161 | blk.17.attn_v.weight      |       0x7f9a5980 |         0x1b8000 |
+|  162 | blk.17.ffn_down.weight    |       0x7fb5d980 |        0x1f80000 |
+|  163 | blk.17.ffn_gate.weight    |       0x81add980 |        0x1810000 |
+|  164 | blk.17.ffn_norm.weight    |       0x832ed980 |           0x4000 |
+|  165 | blk.17.ffn_up.weight      |       0x832f1980 |        0x1810000 |
+|  166 | blk.18.attn_k.weight      |       0x84b01980 |         0x1b8000 |
+|  167 | blk.18.attn_norm.weight   |       0x84cb9980 |           0x4000 |
+|  168 | blk.18.attn_output.weight |       0x84cbd980 |         0x900000 |
+|  169 | blk.18.attn_q.weight      |       0x855bd980 |         0x6e0000 |
+|  170 | blk.18.attn_v.weight      |       0x85c9d980 |         0x240000 |
+|  171 | blk.18.ffn_down.weight    |       0x85edd980 |        0x1f80000 |
+|  172 | blk.18.ffn_gate.weight    |       0x87e5d980 |        0x1810000 |
+|  173 | blk.18.ffn_norm.weight    |       0x8966d980 |           0x4000 |
+|  174 | blk.18.ffn_up.weight      |       0x89671980 |        0x1810000 |
+|  175 | blk.19.attn_k.weight      |       0x8ae81980 |         0x1b8000 |
+|  176 | blk.19.attn_norm.weight   |       0x8b039980 |           0x4000 |
+|  177 | blk.19.attn_output.weight |       0x8b03d980 |         0x900000 |
+|  178 | blk.19.attn_q.weight      |       0x8b93d980 |         0x6e0000 |
+|  179 | blk.19.attn_v.weight      |       0x8c01d980 |         0x240000 |
+|  180 | blk.19.ffn_down.weight    |       0x8c25d980 |        0x1f80000 |
+|  181 | blk.19.ffn_gate.weight    |       0x8e1dd980 |        0x1810000 |
+|  182 | blk.19.ffn_norm.weight    |       0x8f9ed980 |           0x4000 |
+|  183 | blk.19.ffn_up.weight      |       0x8f9f1980 |        0x1810000 |
+|  184 | blk.20.attn_k.weight      |       0x91201980 |         0x1b8000 |
+|  185 | blk.20.attn_norm.weight   |       0x913b9980 |           0x4000 |
+|  186 | blk.20.attn_output.weight |       0x913bd980 |         0x900000 |
+|  187 | blk.20.attn_q.weight      |       0x91cbd980 |         0x6e0000 |
+|  188 | blk.20.attn_v.weight      |       0x9239d980 |         0x240000 |
+|  189 | blk.20.ffn_down.weight    |       0x925dd980 |        0x1f80000 |
+|  190 | blk.20.ffn_gate.weight    |       0x9455d980 |        0x1810000 |
+|  191 | blk.20.ffn_norm.weight    |       0x95d6d980 |           0x4000 |
+|  192 | blk.20.ffn_up.weight      |       0x95d71980 |        0x1810000 |
+|  193 | blk.21.attn_k.weight      |       0x97581980 |         0x1b8000 |
+|  194 | blk.21.attn_norm.weight   |       0x97739980 |           0x4000 |
+|  195 | blk.21.attn_output.weight |       0x9773d980 |         0x900000 |
+|  196 | blk.21.attn_q.weight      |       0x9803d980 |         0x6e0000 |
+|  197 | blk.21.attn_v.weight      |       0x9871d980 |         0x240000 |
+|  198 | blk.21.ffn_down.weight    |       0x9895d980 |        0x1f80000 |
+|  199 | blk.21.ffn_gate.weight    |       0x9a8dd980 |        0x1810000 |
+|  200 | blk.21.ffn_norm.weight    |       0x9c0ed980 |           0x4000 |
+|  201 | blk.21.ffn_up.weight      |       0x9c0f1980 |        0x1810000 |
+|  202 | blk.22.attn_k.weight      |       0x9d901980 |         0x1b8000 |
+|  203 | blk.22.attn_norm.weight   |       0x9dab9980 |           0x4000 |
+|  204 | blk.22.attn_output.weight |       0x9dabd980 |         0x900000 |
+|  205 | blk.22.attn_q.weight      |       0x9e3bd980 |         0x6e0000 |
+|  206 | blk.22.attn_v.weight      |       0x9ea9d980 |         0x240000 |
+|  207 | blk.22.ffn_down.weight    |       0x9ecdd980 |        0x1f80000 |
+|  208 | blk.22.ffn_gate.weight    |       0xa0c5d980 |        0x1810000 |
+|  209 | blk.22.ffn_norm.weight    |       0xa246d980 |           0x4000 |
+|  210 | blk.22.ffn_up.weight      |       0xa2471980 |        0x1810000 |
+|  211 | blk.23.attn_k.weight      |       0xa3c81980 |         0x1b8000 |
+|  212 | blk.23.attn_norm.weight   |       0xa3e39980 |           0x4000 |
+|  213 | blk.23.attn_output.weight |       0xa3e3d980 |         0x900000 |
+|  214 | blk.23.attn_q.weight      |       0xa473d980 |         0x6e0000 |
+|  215 | blk.23.attn_v.weight      |       0xa4e1d980 |         0x240000 |
+|  216 | blk.23.ffn_down.weight    |       0xa505d980 |        0x1f80000 |
+|  217 | blk.23.ffn_gate.weight    |       0xa6fdd980 |        0x1810000 |
+|  218 | blk.23.ffn_norm.weight    |       0xa87ed980 |           0x4000 |
+|  219 | blk.23.ffn_up.weight      |       0xa87f1980 |        0x1810000 |
+|  220 | blk.24.attn_k.weight      |       0xaa001980 |         0x1b8000 |
+|  221 | blk.24.attn_norm.weight   |       0xaa1b9980 |           0x4000 |
+|  222 | blk.24.attn_output.weight |       0xaa1bd980 |         0x900000 |
+|  223 | blk.24.attn_q.weight      |       0xaaabd980 |         0x6e0000 |
+|  224 | blk.24.attn_v.weight      |       0xab19d980 |         0x240000 |
+|  225 | blk.24.ffn_down.weight    |       0xab3dd980 |        0x1f80000 |
+|  226 | blk.24.ffn_gate.weight    |       0xad35d980 |        0x1810000 |
+|  227 | blk.24.ffn_norm.weight    |       0xaeb6d980 |           0x4000 |
+|  228 | blk.24.ffn_up.weight      |       0xaeb71980 |        0x1810000 |
+|  229 | blk.25.attn_k.weight      |       0xb0381980 |         0x1b8000 |
+|  230 | blk.25.attn_norm.weight   |       0xb0539980 |           0x4000 |
+|  231 | blk.25.attn_output.weight |       0xb053d980 |         0x900000 |
+|  232 | blk.25.attn_q.weight      |       0xb0e3d980 |         0x6e0000 |
+|  233 | blk.25.attn_v.weight      |       0xb151d980 |         0x240000 |
+|  234 | blk.25.ffn_down.weight    |       0xb175d980 |        0x1f80000 |
+|  235 | blk.25.ffn_gate.weight    |       0xb36dd980 |        0x1810000 |
+|  236 | blk.25.ffn_norm.weight    |       0xb4eed980 |           0x4000 |
+|  237 | blk.25.ffn_up.weight      |       0xb4ef1980 |        0x1810000 |
+|  238 | blk.26.attn_k.weight      |       0xb6701980 |         0x1b8000 |
+|  239 | blk.26.attn_norm.weight   |       0xb68b9980 |           0x4000 |
+|  240 | blk.26.attn_output.weight |       0xb68bd980 |         0x900000 |
+|  241 | blk.26.attn_q.weight      |       0xb71bd980 |         0x6e0000 |
+|  242 | blk.26.attn_v.weight      |       0xb789d980 |         0x240000 |
+|  243 | blk.26.ffn_down.weight    |       0xb7add980 |        0x1f80000 |
+|  244 | blk.26.ffn_gate.weight    |       0xb9a5d980 |        0x1810000 |
+|  245 | blk.26.ffn_norm.weight    |       0xbb26d980 |           0x4000 |
+|  246 | blk.26.ffn_up.weight      |       0xbb271980 |        0x1810000 |
+|  247 | blk.27.attn_k.weight      |       0xbca81980 |         0x1b8000 |
+|  248 | blk.27.attn_norm.weight   |       0xbcc39980 |           0x4000 |
+|  249 | blk.27.attn_output.weight |       0xbcc3d980 |         0x900000 |
+|  250 | blk.27.attn_q.weight      |       0xbd53d980 |         0x6e0000 |
+|  251 | blk.27.attn_v.weight      |       0xbdc1d980 |         0x240000 |
+|  252 | blk.27.ffn_down.weight    |       0xbde5d980 |        0x1f80000 |
+|  253 | blk.27.ffn_gate.weight    |       0xbfddd980 |        0x1810000 |
+|  254 | blk.27.ffn_norm.weight    |       0xc15ed980 |           0x4000 |
+|  255 | blk.27.ffn_up.weight      |       0xc15f1980 |        0x1810000 |
+|  256 | blk.28.attn_k.weight      |       0xc2e01980 |         0x1b8000 |
+|  257 | blk.28.attn_norm.weight   |       0xc2fb9980 |           0x4000 |
+|  258 | blk.28.attn_output.weight |       0xc2fbd980 |         0x900000 |
+|  259 | blk.28.attn_q.weight      |       0xc38bd980 |         0x6e0000 |
+|  260 | blk.28.attn_v.weight      |       0xc3f9d980 |         0x240000 |
+|  261 | blk.28.ffn_down.weight    |       0xc41dd980 |        0x1f80000 |
+|  262 | blk.28.ffn_gate.weight    |       0xc615d980 |        0x1810000 |
+|  263 | blk.28.ffn_norm.weight    |       0xc796d980 |           0x4000 |
+|  264 | blk.28.ffn_up.weight      |       0xc7971980 |        0x1810000 |
+|  265 | blk.29.attn_k.weight      |       0xc9181980 |         0x1b8000 |
+|  266 | blk.29.attn_norm.weight   |       0xc9339980 |           0x4000 |
+|  267 | blk.29.attn_output.weight |       0xc933d980 |         0x900000 |
+|  268 | blk.29.attn_q.weight      |       0xc9c3d980 |         0x6e0000 |
+|  269 | blk.29.attn_v.weight      |       0xca31d980 |         0x240000 |
+|  270 | blk.29.ffn_down.weight    |       0xca55d980 |        0x1f80000 |
+|  271 | blk.29.ffn_gate.weight    |       0xcc4dd980 |        0x1810000 |
+|  272 | blk.29.ffn_norm.weight    |       0xcdced980 |           0x4000 |
+|  273 | blk.29.ffn_up.weight      |       0xcdcf1980 |        0x1810000 |
+|  274 | blk.30.attn_k.weight      |       0xcf501980 |         0x1b8000 |
+|  275 | blk.30.attn_norm.weight   |       0xcf6b9980 |           0x4000 |
+|  276 | blk.30.attn_output.weight |       0xcf6bd980 |         0x900000 |
+|  277 | blk.30.attn_q.weight      |       0xcffbd980 |         0x6e0000 |
+|  278 | blk.30.attn_v.weight      |       0xd069d980 |         0x240000 |
+|  279 | blk.30.ffn_down.weight    |       0xd08dd980 |        0x1f80000 |
+|  280 | blk.30.ffn_gate.weight    |       0xd285d980 |        0x1810000 |
+|  281 | blk.30.ffn_norm.weight    |       0xd406d980 |           0x4000 |
+|  282 | blk.30.ffn_up.weight      |       0xd4071980 |        0x1810000 |
+|  283 | blk.31.attn_k.weight      |       0xd5881980 |         0x188000 |
+|  284 | blk.31.attn_norm.weight   |       0xd5a09980 |           0x4000 |
+|  285 | blk.31.attn_output.weight |       0xd5a0d980 |         0x900000 |
+|  286 | blk.31.attn_q.weight      |       0xd630d980 |         0x620000 |
+|  287 | blk.31.attn_v.weight      |       0xd692d980 |         0x1b8000 |
+|  288 | blk.31.ffn_down.weight    |       0xd6ae5980 |        0x1f80000 |
+|  289 | blk.31.ffn_gate.weight    |       0xd8a65980 |        0x1810000 |
+|  290 | blk.31.ffn_norm.weight    |       0xda275980 |           0x4000 |
+|  291 | blk.31.ffn_up.weight      |       0xda279980 |        0x1810000 |
+### <a name="base">Base Tensor Group : ~1B Elements</a>
+| T_ID | Tensor Layer Name  | Human Friendly Tensor Layer Name | Elements          | Shape                 | Type  |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:------|
+|    0 | output.weight      | Output (W)                       | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | IQ3_S |
+|    1 | output_norm.weight | Output Normalization (W)         | (  ~4K)      4096 | 4096 x      1 x 1 x 1 | F32   |
+|    2 | rope_freqs.weight  | Rope_Freqs (W)                   | (   64)        64 |   64 x      1 x 1 x 1 | F32   |
+|    3 | token_embd.weight  | Token Embedding (W)              | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | IQ3_S |
+- Total elements in base: ( ~1B) 1050677312
+- Percentage of total elements: 13.08%
+### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|    4 | blk.0.attn_k.weight      | Block 0 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|    5 | blk.0.attn_norm.weight   | Block 0 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|    6 | blk.0.attn_output.weight | Block 0 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|    7 | blk.0.attn_q.weight      | Block 0 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|    8 | blk.0.attn_v.weight      | Block 0 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|    9 | blk.0.ffn_down.weight    | Block 0 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|   10 | blk.0.ffn_gate.weight    | Block 0 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   11 | blk.0.ffn_norm.weight    | Block 0 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   12 | blk.0.ffn_up.weight      | Block 0 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.0: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   13 | blk.1.attn_k.weight      | Block 1 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   14 | blk.1.attn_norm.weight   | Block 1 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   15 | blk.1.attn_output.weight | Block 1 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|   16 | blk.1.attn_q.weight      | Block 1 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   17 | blk.1.attn_v.weight      | Block 1 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   18 | blk.1.ffn_down.weight    | Block 1 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|   19 | blk.1.ffn_gate.weight    | Block 1 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   20 | blk.1.ffn_norm.weight    | Block 1 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   21 | blk.1.ffn_up.weight      | Block 1 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.1: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   22 | blk.2.attn_k.weight      | Block 2 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   23 | blk.2.attn_norm.weight   | Block 2 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   24 | blk.2.attn_output.weight | Block 2 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|   25 | blk.2.attn_q.weight      | Block 2 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   26 | blk.2.attn_v.weight      | Block 2 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   27 | blk.2.ffn_down.weight    | Block 2 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|   28 | blk.2.ffn_gate.weight    | Block 2 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   29 | blk.2.ffn_norm.weight    | Block 2 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   30 | blk.2.ffn_up.weight      | Block 2 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.2: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   31 | blk.3.attn_k.weight      | Block 3 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   32 | blk.3.attn_norm.weight   | Block 3 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   33 | blk.3.attn_output.weight | Block 3 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|   34 | blk.3.attn_q.weight      | Block 3 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   35 | blk.3.attn_v.weight      | Block 3 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   36 | blk.3.ffn_down.weight    | Block 3 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|   37 | blk.3.ffn_gate.weight    | Block 3 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   38 | blk.3.ffn_norm.weight    | Block 3 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   39 | blk.3.ffn_up.weight      | Block 3 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.3: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   40 | blk.4.attn_k.weight      | Block 4 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   41 | blk.4.attn_norm.weight   | Block 4 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   42 | blk.4.attn_output.weight | Block 4 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|   43 | blk.4.attn_q.weight      | Block 4 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   44 | blk.4.attn_v.weight      | Block 4 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   45 | blk.4.ffn_down.weight    | Block 4 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|   46 | blk.4.ffn_gate.weight    | Block 4 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   47 | blk.4.ffn_norm.weight    | Block 4 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   48 | blk.4.ffn_up.weight      | Block 4 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.4: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   49 | blk.5.attn_k.weight      | Block 5 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   50 | blk.5.attn_norm.weight   | Block 5 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   51 | blk.5.attn_output.weight | Block 5 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|   52 | blk.5.attn_q.weight      | Block 5 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   53 | blk.5.attn_v.weight      | Block 5 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   54 | blk.5.ffn_down.weight    | Block 5 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|   55 | blk.5.ffn_gate.weight    | Block 5 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   56 | blk.5.ffn_norm.weight    | Block 5 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   57 | blk.5.ffn_up.weight      | Block 5 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.5: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   58 | blk.6.attn_k.weight      | Block 6 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   59 | blk.6.attn_norm.weight   | Block 6 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   60 | blk.6.attn_output.weight | Block 6 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|   61 | blk.6.attn_q.weight      | Block 6 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   62 | blk.6.attn_v.weight      | Block 6 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   63 | blk.6.ffn_down.weight    | Block 6 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|   64 | blk.6.ffn_gate.weight    | Block 6 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   65 | blk.6.ffn_norm.weight    | Block 6 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   66 | blk.6.ffn_up.weight      | Block 6 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.6: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   67 | blk.7.attn_k.weight      | Block 7 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   68 | blk.7.attn_norm.weight   | Block 7 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   69 | blk.7.attn_output.weight | Block 7 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|   70 | blk.7.attn_q.weight      | Block 7 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   71 | blk.7.attn_v.weight      | Block 7 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   72 | blk.7.ffn_down.weight    | Block 7 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|   73 | blk.7.ffn_gate.weight    | Block 7 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   74 | blk.7.ffn_norm.weight    | Block 7 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   75 | blk.7.ffn_up.weight      | Block 7 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.7: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   76 | blk.8.attn_k.weight      | Block 8 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   77 | blk.8.attn_norm.weight   | Block 8 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   78 | blk.8.attn_output.weight | Block 8 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|   79 | blk.8.attn_q.weight      | Block 8 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   80 | blk.8.attn_v.weight      | Block 8 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   81 | blk.8.ffn_down.weight    | Block 8 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|   82 | blk.8.ffn_gate.weight    | Block 8 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   83 | blk.8.ffn_norm.weight    | Block 8 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   84 | blk.8.ffn_up.weight      | Block 8 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.8: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   85 | blk.9.attn_k.weight      | Block 9 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   86 | blk.9.attn_norm.weight   | Block 9 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   87 | blk.9.attn_output.weight | Block 9 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|   88 | blk.9.attn_q.weight      | Block 9 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   89 | blk.9.attn_v.weight      | Block 9 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   90 | blk.9.ffn_down.weight    | Block 9 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|   91 | blk.9.ffn_gate.weight    | Block 9 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   92 | blk.9.ffn_norm.weight    | Block 9 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   93 | blk.9.ffn_up.weight      | Block 9 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.9: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|   94 | blk.10.attn_k.weight      | Block 10 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   95 | blk.10.attn_norm.weight   | Block 10 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   96 | blk.10.attn_output.weight | Block 10 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|   97 | blk.10.attn_q.weight      | Block 10 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   98 | blk.10.attn_v.weight      | Block 10 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   99 | blk.10.ffn_down.weight    | Block 10 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|  100 | blk.10.ffn_gate.weight    | Block 10 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|  101 | blk.10.ffn_norm.weight    | Block 10 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  102 | blk.10.ffn_up.weight      | Block 10 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.10: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  103 | blk.11.attn_k.weight      | Block 11 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|  104 | blk.11.attn_norm.weight   | Block 11 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  105 | blk.11.attn_output.weight | Block 11 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|  106 | blk.11.attn_q.weight      | Block 11 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|  107 | blk.11.attn_v.weight      | Block 11 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  108 | blk.11.ffn_down.weight    | Block 11 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|  109 | blk.11.ffn_gate.weight    | Block 11 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|  110 | blk.11.ffn_norm.weight    | Block 11 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  111 | blk.11.ffn_up.weight      | Block 11 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.11: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  112 | blk.12.attn_k.weight      | Block 12 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|  113 | blk.12.attn_norm.weight   | Block 12 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  114 | blk.12.attn_output.weight | Block 12 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|  115 | blk.12.attn_q.weight      | Block 12 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|  116 | blk.12.attn_v.weight      | Block 12 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  117 | blk.12.ffn_down.weight    | Block 12 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|  118 | blk.12.ffn_gate.weight    | Block 12 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|  119 | blk.12.ffn_norm.weight    | Block 12 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  120 | blk.12.ffn_up.weight      | Block 12 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.12: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  121 | blk.13.attn_k.weight      | Block 13 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  122 | blk.13.attn_norm.weight   | Block 13 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  123 | blk.13.attn_output.weight | Block 13 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|  124 | blk.13.attn_q.weight      | Block 13 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|  125 | blk.13.attn_v.weight      | Block 13 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL  |
+|  126 | blk.13.ffn_down.weight    | Block 13 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|  127 | blk.13.ffn_gate.weight    | Block 13 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|  128 | blk.13.ffn_norm.weight    | Block 13 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  129 | blk.13.ffn_up.weight      | Block 13 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.13: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  130 | blk.14.attn_k.weight      | Block 14 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  131 | blk.14.attn_norm.weight   | Block 14 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  132 | blk.14.attn_output.weight | Block 14 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|  133 | blk.14.attn_q.weight      | Block 14 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|  134 | blk.14.attn_v.weight      | Block 14 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL  |
+|  135 | blk.14.ffn_down.weight    | Block 14 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|  136 | blk.14.ffn_gate.weight    | Block 14 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|  137 | blk.14.ffn_norm.weight    | Block 14 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  138 | blk.14.ffn_up.weight      | Block 14 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.14: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  139 | blk.15.attn_k.weight      | Block 15 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|  140 | blk.15.attn_norm.weight   | Block 15 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  141 | blk.15.attn_output.weight | Block 15 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|  142 | blk.15.attn_q.weight      | Block 15 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|  143 | blk.15.attn_v.weight      | Block 15 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  144 | blk.15.ffn_down.weight    | Block 15 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|  145 | blk.15.ffn_gate.weight    | Block 15 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|  146 | blk.15.ffn_norm.weight    | Block 15 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  147 | blk.15.ffn_up.weight      | Block 15 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.15: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  148 | blk.16.attn_k.weight      | Block 16 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  149 | blk.16.attn_norm.weight   | Block 16 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  150 | blk.16.attn_output.weight | Block 16 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  151 | blk.16.attn_q.weight      | Block 16 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  152 | blk.16.attn_v.weight      | Block 16 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  153 | blk.16.ffn_down.weight    | Block 16 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  154 | blk.16.ffn_gate.weight    | Block 16 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  155 | blk.16.ffn_norm.weight    | Block 16 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  156 | blk.16.ffn_up.weight      | Block 16 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.16: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  157 | blk.17.attn_k.weight      | Block 17 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|  158 | blk.17.attn_norm.weight   | Block 17 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  159 | blk.17.attn_output.weight | Block 17 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|  160 | blk.17.attn_q.weight      | Block 17 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|  161 | blk.17.attn_v.weight      | Block 17 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  162 | blk.17.ffn_down.weight    | Block 17 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|  163 | blk.17.ffn_gate.weight    | Block 17 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S   |
+|  164 | blk.17.ffn_norm.weight    | Block 17 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  165 | blk.17.ffn_up.weight      | Block 17 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S   |
+- Total elements in blk.17: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  166 | blk.18.attn_k.weight      | Block 18 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  167 | blk.18.attn_norm.weight   | Block 18 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  168 | blk.18.attn_output.weight | Block 18 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  169 | blk.18.attn_q.weight      | Block 18 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  170 | blk.18.attn_v.weight      | Block 18 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  171 | blk.18.ffn_down.weight    | Block 18 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  172 | blk.18.ffn_gate.weight    | Block 18 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  173 | blk.18.ffn_norm.weight    | Block 18 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  174 | blk.18.ffn_up.weight      | Block 18 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.18: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  175 | blk.19.attn_k.weight      | Block 19 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  176 | blk.19.attn_norm.weight   | Block 19 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  177 | blk.19.attn_output.weight | Block 19 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  178 | blk.19.attn_q.weight      | Block 19 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  179 | blk.19.attn_v.weight      | Block 19 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  180 | blk.19.ffn_down.weight    | Block 19 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  181 | blk.19.ffn_gate.weight    | Block 19 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  182 | blk.19.ffn_norm.weight    | Block 19 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  183 | blk.19.ffn_up.weight      | Block 19 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.19: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  184 | blk.20.attn_k.weight      | Block 20 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  185 | blk.20.attn_norm.weight   | Block 20 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  186 | blk.20.attn_output.weight | Block 20 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  187 | blk.20.attn_q.weight      | Block 20 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  188 | blk.20.attn_v.weight      | Block 20 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  189 | blk.20.ffn_down.weight    | Block 20 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  190 | blk.20.ffn_gate.weight    | Block 20 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  191 | blk.20.ffn_norm.weight    | Block 20 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  192 | blk.20.ffn_up.weight      | Block 20 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.20: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  193 | blk.21.attn_k.weight      | Block 21 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  194 | blk.21.attn_norm.weight   | Block 21 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  195 | blk.21.attn_output.weight | Block 21 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  196 | blk.21.attn_q.weight      | Block 21 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  197 | blk.21.attn_v.weight      | Block 21 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  198 | blk.21.ffn_down.weight    | Block 21 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  199 | blk.21.ffn_gate.weight    | Block 21 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  200 | blk.21.ffn_norm.weight    | Block 21 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  201 | blk.21.ffn_up.weight      | Block 21 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.21: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  202 | blk.22.attn_k.weight      | Block 22 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  203 | blk.22.attn_norm.weight   | Block 22 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  204 | blk.22.attn_output.weight | Block 22 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  205 | blk.22.attn_q.weight      | Block 22 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  206 | blk.22.attn_v.weight      | Block 22 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  207 | blk.22.ffn_down.weight    | Block 22 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  208 | blk.22.ffn_gate.weight    | Block 22 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  209 | blk.22.ffn_norm.weight    | Block 22 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  210 | blk.22.ffn_up.weight      | Block 22 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.22: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  211 | blk.23.attn_k.weight      | Block 23 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  212 | blk.23.attn_norm.weight   | Block 23 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  213 | blk.23.attn_output.weight | Block 23 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  214 | blk.23.attn_q.weight      | Block 23 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  215 | blk.23.attn_v.weight      | Block 23 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  216 | blk.23.ffn_down.weight    | Block 23 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  217 | blk.23.ffn_gate.weight    | Block 23 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  218 | blk.23.ffn_norm.weight    | Block 23 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  219 | blk.23.ffn_up.weight      | Block 23 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.23: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  220 | blk.24.attn_k.weight      | Block 24 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  221 | blk.24.attn_norm.weight   | Block 24 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  222 | blk.24.attn_output.weight | Block 24 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  223 | blk.24.attn_q.weight      | Block 24 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  224 | blk.24.attn_v.weight      | Block 24 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  225 | blk.24.ffn_down.weight    | Block 24 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  226 | blk.24.ffn_gate.weight    | Block 24 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  227 | blk.24.ffn_norm.weight    | Block 24 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  228 | blk.24.ffn_up.weight      | Block 24 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.24: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  229 | blk.25.attn_k.weight      | Block 25 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  230 | blk.25.attn_norm.weight   | Block 25 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  231 | blk.25.attn_output.weight | Block 25 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  232 | blk.25.attn_q.weight      | Block 25 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  233 | blk.25.attn_v.weight      | Block 25 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  234 | blk.25.ffn_down.weight    | Block 25 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  235 | blk.25.ffn_gate.weight    | Block 25 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  236 | blk.25.ffn_norm.weight    | Block 25 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  237 | blk.25.ffn_up.weight      | Block 25 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.25: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  238 | blk.26.attn_k.weight      | Block 26 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  239 | blk.26.attn_norm.weight   | Block 26 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  240 | blk.26.attn_output.weight | Block 26 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  241 | blk.26.attn_q.weight      | Block 26 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  242 | blk.26.attn_v.weight      | Block 26 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  243 | blk.26.ffn_down.weight    | Block 26 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  244 | blk.26.ffn_gate.weight    | Block 26 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  245 | blk.26.ffn_norm.weight    | Block 26 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  246 | blk.26.ffn_up.weight      | Block 26 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.26: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  247 | blk.27.attn_k.weight      | Block 27 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  248 | blk.27.attn_norm.weight   | Block 27 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  249 | blk.27.attn_output.weight | Block 27 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  250 | blk.27.attn_q.weight      | Block 27 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  251 | blk.27.attn_v.weight      | Block 27 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  252 | blk.27.ffn_down.weight    | Block 27 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  253 | blk.27.ffn_gate.weight    | Block 27 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  254 | blk.27.ffn_norm.weight    | Block 27 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  255 | blk.27.ffn_up.weight      | Block 27 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.27: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  256 | blk.28.attn_k.weight      | Block 28 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  257 | blk.28.attn_norm.weight   | Block 28 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  258 | blk.28.attn_output.weight | Block 28 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  259 | blk.28.attn_q.weight      | Block 28 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  260 | blk.28.attn_v.weight      | Block 28 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  261 | blk.28.ffn_down.weight    | Block 28 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  262 | blk.28.ffn_gate.weight    | Block 28 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  263 | blk.28.ffn_norm.weight    | Block 28 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  264 | blk.28.ffn_up.weight      | Block 28 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.28: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  265 | blk.29.attn_k.weight      | Block 29 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  266 | blk.29.attn_norm.weight   | Block 29 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  267 | blk.29.attn_output.weight | Block 29 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  268 | blk.29.attn_q.weight      | Block 29 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  269 | blk.29.attn_v.weight      | Block 29 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  270 | blk.29.ffn_down.weight    | Block 29 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  271 | blk.29.ffn_gate.weight    | Block 29 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  272 | blk.29.ffn_norm.weight    | Block 29 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  273 | blk.29.ffn_up.weight      | Block 29 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.29: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  274 | blk.30.attn_k.weight      | Block 30 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  275 | blk.30.attn_norm.weight   | Block 30 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  276 | blk.30.attn_output.weight | Block 30 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K   |
+|  277 | blk.30.attn_q.weight      | Block 30 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  278 | blk.30.attn_v.weight      | Block 30 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  279 | blk.30.ffn_down.weight    | Block 30 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  280 | blk.30.ffn_gate.weight    | Block 30 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  281 | blk.30.ffn_norm.weight    | Block 30 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  282 | blk.30.ffn_up.weight      | Block 30 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.30: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  283 | blk.31.attn_k.weight      | Block 31 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|  284 | blk.31.attn_norm.weight   | Block 31 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  285 | blk.31.attn_output.weight | Block 31 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K    |
+|  286 | blk.31.attn_q.weight      | Block 31 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|  287 | blk.31.attn_v.weight      | Block 31 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  288 | blk.31.ffn_down.weight    | Block 31 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|  289 | blk.31.ffn_gate.weight    | Block 31 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S   |
+|  290 | blk.31.ffn_norm.weight    | Block 31 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  291 | blk.31.ffn_up.weight      | Block 31 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S   |
+- Total elements in blk.31: (~218M) 218112000
+- Percentage of total elements: 2.72%

scores/Llama-Guard-3-8B-IQ3_S.md ADDED Viewed

	@@ -0,0 +1,978 @@

+# Llama-Guard-3-8B-IQ3_S.gguf - GGUF Internal File Dump
+- Endian: LITTLE endian
+## Key Value Metadata Store
+There are 39 key-value pairs in this file
+| POS | TYPE     |  Count | Key                                    | Value                                                               |
+|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
+|   1 | UINT32   |      1 | GGUF.version                           | 3                                                                   |
+|   2 | UINT64   |      1 | GGUF.tensor_count                      | 292                                                                 |
+|   3 | UINT64   |      1 | GGUF.kv_count                          | 36                                                                  |
+|   4 | STRING   |      1 | general.architecture                   | `llama`                                                             |
+|   5 | STRING   |      1 | general.type                           | `model`                                                             |
+|   6 | STRING   |      1 | general.name                           | `Llama Guard 3 8B`                                                  |
+|   7 | STRING   |      1 | general.basename                       | `Llama-Guard-3`                                                     |
+|   8 | STRING   |      1 | general.size_label                     | `8B`                                                                |
+|   9 | STRING   |      1 | general.license                        | `llama3.1`                                                          |
+|  10 | UINT32   |      1 | general.base_model.count               | 1                                                                   |
+|  11 | STRING   |      1 | general.base_model.0.name              | `Meta Llama 3.1 8B`                                                 |
+|  12 | STRING   |      1 | general.base_model.0.organization      | `Meta Llama`                                                        |
+|  13 | STRING   |      1 | general.base_model.0.repo_url          | `https://huggingface.co/meta-llama/Meta-Llama-3.1-8B`               |
+|  14 | [STRING] |      6 | general.tags                           | [ `facebook`, `meta`, `pytorch`, `llama`, `llama-3`, ... ]          |
+|  15 | [STRING] |      1 | general.languages                      | [ `en` ]                                                            |
+|  16 | UINT32   |      1 | llama.block_count                      | 32                                                                  |
+|  17 | UINT32   |      1 | llama.context_length                   | 131072                                                              |
+|  18 | UINT32   |      1 | llama.embedding_length                 | 4096                                                                |
+|  19 | UINT32   |      1 | llama.feed_forward_length              | 14336                                                               |
+|  20 | UINT32   |      1 | llama.attention.head_count             | 32                                                                  |
+|  21 | UINT32   |      1 | llama.attention.head_count_kv          | 8                                                                   |
+|  22 | FLOAT32  |      1 | llama.rope.freq_base                   | 500000.0                                                            |
+|  23 | FLOAT32  |      1 | llama.attention.layer_norm_rms_epsilon | 1e-05                                                               |
+|  24 | UINT32   |      1 | llama.vocab_size                       | 128256                                                              |
+|  25 | UINT32   |      1 | llama.rope.dimension_count             | 128                                                                 |
+|  26 | STRING   |      1 | tokenizer.ggml.model                   | `gpt2`                                                              |
+|  27 | STRING   |      1 | tokenizer.ggml.pre                     | `smaug-bpe`                                                         |
+|  28 | [STRING] | 128256 | tokenizer.ggml.tokens                  | [ `!`, `"`, `#`, `$`, `%`, ... ]                                    |
+|  29 | [INT32]  | 128256 | tokenizer.ggml.token_type              | [ 1, 1, 1, 1, 1, 1, 1, ... ]                                        |
+|  30 | [STRING] | 280147 | tokenizer.ggml.merges                  | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]                    |
+|  31 | UINT32   |      1 | tokenizer.ggml.bos_token_id            | 128000                                                              |
+|  32 | UINT32   |      1 | tokenizer.ggml.eos_token_id            | 128009                                                              |
+|  33 | STRING   |      1 | tokenizer.chat_template                | `{% if messages|length % 2 == 0`...`assistant<|end_header_id|>" }}` |
+|  34 | UINT32   |      1 | general.quantization_version           | 2                                                                   |
+|  35 | UINT32   |      1 | general.file_type                      | 26                                                                  |
+|  36 | STRING   |      1 | quantize.imatrix.file                  | `./imatrix/imatrix-Llama-Guard-3-8B-small.dat`                      |
+|  37 | STRING   |      1 | quantize.imatrix.dataset               | `../../datasets/imatrix/calibration_eur_small.txt`                  |
+|  38 | INT32    |      1 | quantize.imatrix.entries_count         | 224                                                                 |
+|  39 | INT32    |      1 | quantize.imatrix.chunks_count          | 962                                                                 |
+## Tensors Overview ~8B Elements
+Total number of elements in all tensors: 8030261312 Elements
+- [Llama-Guard-3-8B-IQ3\_S.gguf - GGUF Internal File Dump](#llama-guard-3-8b-iq3_sgguf---gguf-internal-file-dump)
+  - [Key Value Metadata Store](#key-value-metadata-store)
+  - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
+    - [Tensor Data Offset](#tensor-data-offset)
+    - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
+    - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
+    - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
+    - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
+    - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
+    - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
+    - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
+    - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
+    - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
+    - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
+    - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
+    - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
+    - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
+    - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
+    - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
+    - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
+    - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
+    - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
+    - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
+    - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
+    - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
+    - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
+    - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
+    - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
+    - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
+    - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
+    - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
+    - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
+    - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
+    - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
+    - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
+    - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
+    - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
+### Tensor Data Offset
+This table contains the offset and data segment relative to start of file
+| T_ID | Tensor Layer Name         |  Data Offset (B) |    Data Size (B) |
+|-----:|:--------------------------|-----------------:|-----------------:|
+|    0 | output.weight             |         0x779880 |        0xbfca000 |
+|    1 | output_norm.weight        |        0xc743880 |           0x4000 |
+|    2 | rope_freqs.weight         |        0xc747880 |            0x100 |
+|    3 | token_embd.weight         |        0xc747980 |        0xbfca000 |
+|    4 | blk.0.attn_k.weight       |       0x18711980 |         0x188000 |
+|    5 | blk.0.attn_norm.weight    |       0x18899980 |           0x4000 |
+|    6 | blk.0.attn_output.weight  |       0x1889d980 |         0x6e0000 |
+|    7 | blk.0.attn_q.weight       |       0x18f7d980 |         0x620000 |
+|    8 | blk.0.attn_v.weight       |       0x1959d980 |         0x1b8000 |
+|    9 | blk.0.ffn_down.weight     |       0x19755980 |        0x1810000 |
+|   10 | blk.0.ffn_gate.weight     |       0x1af65980 |        0x1570000 |
+|   11 | blk.0.ffn_norm.weight     |       0x1c4d5980 |           0x4000 |
+|   12 | blk.0.ffn_up.weight       |       0x1c4d9980 |        0x1570000 |
+|   13 | blk.1.attn_k.weight       |       0x1da49980 |         0x188000 |
+|   14 | blk.1.attn_norm.weight    |       0x1dbd1980 |           0x4000 |
+|   15 | blk.1.attn_output.weight  |       0x1dbd5980 |         0x6e0000 |
+|   16 | blk.1.attn_q.weight       |       0x1e2b5980 |         0x620000 |
+|   17 | blk.1.attn_v.weight       |       0x1e8d5980 |         0x1b8000 |
+|   18 | blk.1.ffn_down.weight     |       0x1ea8d980 |        0x1f80000 |
+|   19 | blk.1.ffn_gate.weight     |       0x20a0d980 |        0x1570000 |
+|   20 | blk.1.ffn_norm.weight     |       0x21f7d980 |           0x4000 |
+|   21 | blk.1.ffn_up.weight       |       0x21f81980 |        0x1570000 |
+|   22 | blk.2.attn_k.weight       |       0x234f1980 |         0x188000 |
+|   23 | blk.2.attn_norm.weight    |       0x23679980 |           0x4000 |
+|   24 | blk.2.attn_output.weight  |       0x2367d980 |         0x6e0000 |
+|   25 | blk.2.attn_q.weight       |       0x23d5d980 |         0x620000 |
+|   26 | blk.2.attn_v.weight       |       0x2437d980 |         0x1b8000 |
+|   27 | blk.2.ffn_down.weight     |       0x24535980 |        0x1810000 |
+|   28 | blk.2.ffn_gate.weight     |       0x25d45980 |        0x1570000 |
+|   29 | blk.2.ffn_norm.weight     |       0x272b5980 |           0x4000 |
+|   30 | blk.2.ffn_up.weight       |       0x272b9980 |        0x1570000 |
+|   31 | blk.3.attn_k.weight       |       0x28829980 |         0x188000 |
+|   32 | blk.3.attn_norm.weight    |       0x289b1980 |           0x4000 |
+|   33 | blk.3.attn_output.weight  |       0x289b5980 |         0x6e0000 |
+|   34 | blk.3.attn_q.weight       |       0x29095980 |         0x620000 |
+|   35 | blk.3.attn_v.weight       |       0x296b5980 |         0x1b8000 |
+|   36 | blk.3.ffn_down.weight     |       0x2986d980 |        0x1810000 |
+|   37 | blk.3.ffn_gate.weight     |       0x2b07d980 |        0x1570000 |
+|   38 | blk.3.ffn_norm.weight     |       0x2c5ed980 |           0x4000 |
+|   39 | blk.3.ffn_up.weight       |       0x2c5f1980 |        0x1570000 |
+|   40 | blk.4.attn_k.weight       |       0x2db61980 |         0x188000 |
+|   41 | blk.4.attn_norm.weight    |       0x2dce9980 |           0x4000 |
+|   42 | blk.4.attn_output.weight  |       0x2dced980 |         0x6e0000 |
+|   43 | blk.4.attn_q.weight       |       0x2e3cd980 |         0x620000 |
+|   44 | blk.4.attn_v.weight       |       0x2e9ed980 |         0x1b8000 |
+|   45 | blk.4.ffn_down.weight     |       0x2eba5980 |        0x1810000 |
+|   46 | blk.4.ffn_gate.weight     |       0x303b5980 |        0x1570000 |
+|   47 | blk.4.ffn_norm.weight     |       0x31925980 |           0x4000 |
+|   48 | blk.4.ffn_up.weight       |       0x31929980 |        0x1570000 |
+|   49 | blk.5.attn_k.weight       |       0x32e99980 |         0x188000 |
+|   50 | blk.5.attn_norm.weight    |       0x33021980 |           0x4000 |
+|   51 | blk.5.attn_output.weight  |       0x33025980 |         0x6e0000 |
+|   52 | blk.5.attn_q.weight       |       0x33705980 |         0x620000 |
+|   53 | blk.5.attn_v.weight       |       0x33d25980 |         0x1b8000 |
+|   54 | blk.5.ffn_down.weight     |       0x33edd980 |        0x1810000 |
+|   55 | blk.5.ffn_gate.weight     |       0x356ed980 |        0x1570000 |
+|   56 | blk.5.ffn_norm.weight     |       0x36c5d980 |           0x4000 |
+|   57 | blk.5.ffn_up.weight       |       0x36c61980 |        0x1570000 |
+|   58 | blk.6.attn_k.weight       |       0x381d1980 |         0x188000 |
+|   59 | blk.6.attn_norm.weight    |       0x38359980 |           0x4000 |
+|   60 | blk.6.attn_output.weight  |       0x3835d980 |         0x6e0000 |
+|   61 | blk.6.attn_q.weight       |       0x38a3d980 |         0x620000 |
+|   62 | blk.6.attn_v.weight       |       0x3905d980 |         0x1b8000 |
+|   63 | blk.6.ffn_down.weight     |       0x39215980 |        0x1810000 |
+|   64 | blk.6.ffn_gate.weight     |       0x3aa25980 |        0x1570000 |
+|   65 | blk.6.ffn_norm.weight     |       0x3bf95980 |           0x4000 |
+|   66 | blk.6.ffn_up.weight       |       0x3bf99980 |        0x1570000 |
+|   67 | blk.7.attn_k.weight       |       0x3d509980 |         0x188000 |
+|   68 | blk.7.attn_norm.weight    |       0x3d691980 |           0x4000 |
+|   69 | blk.7.attn_output.weight  |       0x3d695980 |         0x6e0000 |
+|   70 | blk.7.attn_q.weight       |       0x3dd75980 |         0x620000 |
+|   71 | blk.7.attn_v.weight       |       0x3e395980 |         0x1b8000 |
+|   72 | blk.7.ffn_down.weight     |       0x3e54d980 |        0x1810000 |
+|   73 | blk.7.ffn_gate.weight     |       0x3fd5d980 |        0x1570000 |
+|   74 | blk.7.ffn_norm.weight     |       0x412cd980 |           0x4000 |
+|   75 | blk.7.ffn_up.weight       |       0x412d1980 |        0x1570000 |
+|   76 | blk.8.attn_k.weight       |       0x42841980 |         0x188000 |
+|   77 | blk.8.attn_norm.weight    |       0x429c9980 |           0x4000 |
+|   78 | blk.8.attn_output.weight  |       0x429cd980 |         0x6e0000 |
+|   79 | blk.8.attn_q.weight       |       0x430ad980 |         0x620000 |
+|   80 | blk.8.attn_v.weight       |       0x436cd980 |         0x1b8000 |
+|   81 | blk.8.ffn_down.weight     |       0x43885980 |        0x1810000 |
+|   82 | blk.8.ffn_gate.weight     |       0x45095980 |        0x1570000 |
+|   83 | blk.8.ffn_norm.weight     |       0x46605980 |           0x4000 |
+|   84 | blk.8.ffn_up.weight       |       0x46609980 |        0x1570000 |
+|   85 | blk.9.attn_k.weight       |       0x47b79980 |         0x188000 |
+|   86 | blk.9.attn_norm.weight    |       0x47d01980 |           0x4000 |
+|   87 | blk.9.attn_output.weight  |       0x47d05980 |         0x6e0000 |
+|   88 | blk.9.attn_q.weight       |       0x483e5980 |         0x620000 |
+|   89 | blk.9.attn_v.weight       |       0x48a05980 |         0x1b8000 |
+|   90 | blk.9.ffn_down.weight     |       0x48bbd980 |        0x1810000 |
+|   91 | blk.9.ffn_gate.weight     |       0x4a3cd980 |        0x1570000 |
+|   92 | blk.9.ffn_norm.weight     |       0x4b93d980 |           0x4000 |
+|   93 | blk.9.ffn_up.weight       |       0x4b941980 |        0x1570000 |
+|   94 | blk.10.attn_k.weight      |       0x4ceb1980 |         0x188000 |
+|   95 | blk.10.attn_norm.weight   |       0x4d039980 |           0x4000 |
+|   96 | blk.10.attn_output.weight |       0x4d03d980 |         0x6e0000 |
+|   97 | blk.10.attn_q.weight      |       0x4d71d980 |         0x620000 |
+|   98 | blk.10.attn_v.weight      |       0x4dd3d980 |         0x1b8000 |
+|   99 | blk.10.ffn_down.weight    |       0x4def5980 |        0x1810000 |
+|  100 | blk.10.ffn_gate.weight    |       0x4f705980 |        0x1570000 |
+|  101 | blk.10.ffn_norm.weight    |       0x50c75980 |           0x4000 |
+|  102 | blk.10.ffn_up.weight      |       0x50c79980 |        0x1570000 |
+|  103 | blk.11.attn_k.weight      |       0x521e9980 |         0x188000 |
+|  104 | blk.11.attn_norm.weight   |       0x52371980 |           0x4000 |
+|  105 | blk.11.attn_output.weight |       0x52375980 |         0x6e0000 |
+|  106 | blk.11.attn_q.weight      |       0x52a55980 |         0x620000 |
+|  107 | blk.11.attn_v.weight      |       0x53075980 |         0x1b8000 |
+|  108 | blk.11.ffn_down.weight    |       0x5322d980 |        0x1810000 |
+|  109 | blk.11.ffn_gate.weight    |       0x54a3d980 |        0x1570000 |
+|  110 | blk.11.ffn_norm.weight    |       0x55fad980 |           0x4000 |
+|  111 | blk.11.ffn_up.weight      |       0x55fb1980 |        0x1570000 |
+|  112 | blk.12.attn_k.weight      |       0x57521980 |         0x188000 |
+|  113 | blk.12.attn_norm.weight   |       0x576a9980 |           0x4000 |
+|  114 | blk.12.attn_output.weight |       0x576ad980 |         0x6e0000 |
+|  115 | blk.12.attn_q.weight      |       0x57d8d980 |         0x620000 |
+|  116 | blk.12.attn_v.weight      |       0x583ad980 |         0x1b8000 |
+|  117 | blk.12.ffn_down.weight    |       0x58565980 |        0x1810000 |
+|  118 | blk.12.ffn_gate.weight    |       0x59d75980 |        0x1570000 |
+|  119 | blk.12.ffn_norm.weight    |       0x5b2e5980 |           0x4000 |
+|  120 | blk.12.ffn_up.weight      |       0x5b2e9980 |        0x1570000 |
+|  121 | blk.13.attn_k.weight      |       0x5c859980 |         0x1b8000 |
+|  122 | blk.13.attn_norm.weight   |       0x5ca11980 |           0x4000 |
+|  123 | blk.13.attn_output.weight |       0x5ca15980 |         0x6e0000 |
+|  124 | blk.13.attn_q.weight      |       0x5d0f5980 |         0x6e0000 |
+|  125 | blk.13.attn_v.weight      |       0x5d7d5980 |         0x1b8000 |
+|  126 | blk.13.ffn_down.weight    |       0x5d98d980 |        0x1810000 |
+|  127 | blk.13.ffn_gate.weight    |       0x5f19d980 |        0x1570000 |
+|  128 | blk.13.ffn_norm.weight    |       0x6070d980 |           0x4000 |
+|  129 | blk.13.ffn_up.weight      |       0x60711980 |        0x1570000 |
+|  130 | blk.14.attn_k.weight      |       0x61c81980 |         0x1b8000 |
+|  131 | blk.14.attn_norm.weight   |       0x61e39980 |           0x4000 |
+|  132 | blk.14.attn_output.weight |       0x61e3d980 |         0x6e0000 |
+|  133 | blk.14.attn_q.weight      |       0x6251d980 |         0x6e0000 |
+|  134 | blk.14.attn_v.weight      |       0x62bfd980 |         0x1b8000 |
+|  135 | blk.14.ffn_down.weight    |       0x62db5980 |        0x1810000 |
+|  136 | blk.14.ffn_gate.weight    |       0x645c5980 |        0x1570000 |
+|  137 | blk.14.ffn_norm.weight    |       0x65b35980 |           0x4000 |
+|  138 | blk.14.ffn_up.weight      |       0x65b39980 |        0x1570000 |
+|  139 | blk.15.attn_k.weight      |       0x670a9980 |         0x188000 |
+|  140 | blk.15.attn_norm.weight   |       0x67231980 |           0x4000 |
+|  141 | blk.15.attn_output.weight |       0x67235980 |         0x6e0000 |
+|  142 | blk.15.attn_q.weight      |       0x67915980 |         0x620000 |
+|  143 | blk.15.attn_v.weight      |       0x67f35980 |         0x1b8000 |
+|  144 | blk.15.ffn_down.weight    |       0x680ed980 |        0x1810000 |
+|  145 | blk.15.ffn_gate.weight    |       0x698fd980 |        0x1570000 |
+|  146 | blk.15.ffn_norm.weight    |       0x6ae6d980 |           0x4000 |
+|  147 | blk.15.ffn_up.weight      |       0x6ae71980 |        0x1570000 |
+|  148 | blk.16.attn_k.weight      |       0x6c3e1980 |         0x1b8000 |
+|  149 | blk.16.attn_norm.weight   |       0x6c599980 |           0x4000 |
+|  150 | blk.16.attn_output.weight |       0x6c59d980 |         0x6e0000 |
+|  151 | blk.16.attn_q.weight      |       0x6cc7d980 |         0x6e0000 |
+|  152 | blk.16.attn_v.weight      |       0x6d35d980 |         0x1b8000 |
+|  153 | blk.16.ffn_down.weight    |       0x6d515980 |        0x1810000 |
+|  154 | blk.16.ffn_gate.weight    |       0x6ed25980 |        0x1810000 |
+|  155 | blk.16.ffn_norm.weight    |       0x70535980 |           0x4000 |
+|  156 | blk.16.ffn_up.weight      |       0x70539980 |        0x1810000 |
+|  157 | blk.17.attn_k.weight      |       0x71d49980 |         0x188000 |
+|  158 | blk.17.attn_norm.weight   |       0x71ed1980 |           0x4000 |
+|  159 | blk.17.attn_output.weight |       0x71ed5980 |         0x6e0000 |
+|  160 | blk.17.attn_q.weight      |       0x725b5980 |         0x620000 |
+|  161 | blk.17.attn_v.weight      |       0x72bd5980 |         0x1b8000 |
+|  162 | blk.17.ffn_down.weight    |       0x72d8d980 |        0x1f80000 |
+|  163 | blk.17.ffn_gate.weight    |       0x74d0d980 |        0x1810000 |
+|  164 | blk.17.ffn_norm.weight    |       0x7651d980 |           0x4000 |
+|  165 | blk.17.ffn_up.weight      |       0x76521980 |        0x1810000 |
+|  166 | blk.18.attn_k.weight      |       0x77d31980 |         0x1b8000 |
+|  167 | blk.18.attn_norm.weight   |       0x77ee9980 |           0x4000 |
+|  168 | blk.18.attn_output.weight |       0x77eed980 |         0x6e0000 |
+|  169 | blk.18.attn_q.weight      |       0x785cd980 |         0x6e0000 |
+|  170 | blk.18.attn_v.weight      |       0x78cad980 |         0x1b8000 |
+|  171 | blk.18.ffn_down.weight    |       0x78e65980 |        0x1f80000 |
+|  172 | blk.18.ffn_gate.weight    |       0x7ade5980 |        0x1810000 |
+|  173 | blk.18.ffn_norm.weight    |       0x7c5f5980 |           0x4000 |
+|  174 | blk.18.ffn_up.weight      |       0x7c5f9980 |        0x1810000 |
+|  175 | blk.19.attn_k.weight      |       0x7de09980 |         0x1b8000 |
+|  176 | blk.19.attn_norm.weight   |       0x7dfc1980 |           0x4000 |
+|  177 | blk.19.attn_output.weight |       0x7dfc5980 |         0x6e0000 |
+|  178 | blk.19.attn_q.weight      |       0x7e6a5980 |         0x6e0000 |
+|  179 | blk.19.attn_v.weight      |       0x7ed85980 |         0x1b8000 |
+|  180 | blk.19.ffn_down.weight    |       0x7ef3d980 |        0x1f80000 |
+|  181 | blk.19.ffn_gate.weight    |       0x80ebd980 |        0x1810000 |
+|  182 | blk.19.ffn_norm.weight    |       0x826cd980 |           0x4000 |
+|  183 | blk.19.ffn_up.weight      |       0x826d1980 |        0x1810000 |
+|  184 | blk.20.attn_k.weight      |       0x83ee1980 |         0x1b8000 |
+|  185 | blk.20.attn_norm.weight   |       0x84099980 |           0x4000 |
+|  186 | blk.20.attn_output.weight |       0x8409d980 |         0x6e0000 |
+|  187 | blk.20.attn_q.weight      |       0x8477d980 |         0x6e0000 |
+|  188 | blk.20.attn_v.weight      |       0x84e5d980 |         0x1b8000 |
+|  189 | blk.20.ffn_down.weight    |       0x85015980 |        0x1f80000 |
+|  190 | blk.20.ffn_gate.weight    |       0x86f95980 |        0x1810000 |
+|  191 | blk.20.ffn_norm.weight    |       0x887a5980 |           0x4000 |
+|  192 | blk.20.ffn_up.weight      |       0x887a9980 |        0x1810000 |
+|  193 | blk.21.attn_k.weight      |       0x89fb9980 |         0x1b8000 |
+|  194 | blk.21.attn_norm.weight   |       0x8a171980 |           0x4000 |
+|  195 | blk.21.attn_output.weight |       0x8a175980 |         0x6e0000 |
+|  196 | blk.21.attn_q.weight      |       0x8a855980 |         0x6e0000 |
+|  197 | blk.21.attn_v.weight      |       0x8af35980 |         0x1b8000 |
+|  198 | blk.21.ffn_down.weight    |       0x8b0ed980 |        0x1f80000 |
+|  199 | blk.21.ffn_gate.weight    |       0x8d06d980 |        0x1810000 |
+|  200 | blk.21.ffn_norm.weight    |       0x8e87d980 |           0x4000 |
+|  201 | blk.21.ffn_up.weight      |       0x8e881980 |        0x1810000 |
+|  202 | blk.22.attn_k.weight      |       0x90091980 |         0x1b8000 |
+|  203 | blk.22.attn_norm.weight   |       0x90249980 |           0x4000 |
+|  204 | blk.22.attn_output.weight |       0x9024d980 |         0x6e0000 |
+|  205 | blk.22.attn_q.weight      |       0x9092d980 |         0x6e0000 |
+|  206 | blk.22.attn_v.weight      |       0x9100d980 |         0x1b8000 |
+|  207 | blk.22.ffn_down.weight    |       0x911c5980 |        0x1f80000 |
+|  208 | blk.22.ffn_gate.weight    |       0x93145980 |        0x1810000 |
+|  209 | blk.22.ffn_norm.weight    |       0x94955980 |           0x4000 |
+|  210 | blk.22.ffn_up.weight      |       0x94959980 |        0x1810000 |
+|  211 | blk.23.attn_k.weight      |       0x96169980 |         0x1b8000 |
+|  212 | blk.23.attn_norm.weight   |       0x96321980 |           0x4000 |
+|  213 | blk.23.attn_output.weight |       0x96325980 |         0x6e0000 |
+|  214 | blk.23.attn_q.weight      |       0x96a05980 |         0x6e0000 |
+|  215 | blk.23.attn_v.weight      |       0x970e5980 |         0x1b8000 |
+|  216 | blk.23.ffn_down.weight    |       0x9729d980 |        0x1f80000 |
+|  217 | blk.23.ffn_gate.weight    |       0x9921d980 |        0x1810000 |
+|  218 | blk.23.ffn_norm.weight    |       0x9aa2d980 |           0x4000 |
+|  219 | blk.23.ffn_up.weight      |       0x9aa31980 |        0x1810000 |
+|  220 | blk.24.attn_k.weight      |       0x9c241980 |         0x1b8000 |
+|  221 | blk.24.attn_norm.weight   |       0x9c3f9980 |           0x4000 |
+|  222 | blk.24.attn_output.weight |       0x9c3fd980 |         0x6e0000 |
+|  223 | blk.24.attn_q.weight      |       0x9cadd980 |         0x6e0000 |
+|  224 | blk.24.attn_v.weight      |       0x9d1bd980 |         0x1b8000 |
+|  225 | blk.24.ffn_down.weight    |       0x9d375980 |        0x1f80000 |
+|  226 | blk.24.ffn_gate.weight    |       0x9f2f5980 |        0x1810000 |
+|  227 | blk.24.ffn_norm.weight    |       0xa0b05980 |           0x4000 |
+|  228 | blk.24.ffn_up.weight      |       0xa0b09980 |        0x1810000 |
+|  229 | blk.25.attn_k.weight      |       0xa2319980 |         0x1b8000 |
+|  230 | blk.25.attn_norm.weight   |       0xa24d1980 |           0x4000 |
+|  231 | blk.25.attn_output.weight |       0xa24d5980 |         0x6e0000 |
+|  232 | blk.25.attn_q.weight      |       0xa2bb5980 |         0x6e0000 |
+|  233 | blk.25.attn_v.weight      |       0xa3295980 |         0x1b8000 |
+|  234 | blk.25.ffn_down.weight    |       0xa344d980 |        0x1f80000 |
+|  235 | blk.25.ffn_gate.weight    |       0xa53cd980 |        0x1810000 |
+|  236 | blk.25.ffn_norm.weight    |       0xa6bdd980 |           0x4000 |
+|  237 | blk.25.ffn_up.weight      |       0xa6be1980 |        0x1810000 |
+|  238 | blk.26.attn_k.weight      |       0xa83f1980 |         0x1b8000 |
+|  239 | blk.26.attn_norm.weight   |       0xa85a9980 |           0x4000 |
+|  240 | blk.26.attn_output.weight |       0xa85ad980 |         0x6e0000 |
+|  241 | blk.26.attn_q.weight      |       0xa8c8d980 |         0x6e0000 |
+|  242 | blk.26.attn_v.weight      |       0xa936d980 |         0x1b8000 |
+|  243 | blk.26.ffn_down.weight    |       0xa9525980 |        0x1f80000 |
+|  244 | blk.26.ffn_gate.weight    |       0xab4a5980 |        0x1810000 |
+|  245 | blk.26.ffn_norm.weight    |       0xaccb5980 |           0x4000 |
+|  246 | blk.26.ffn_up.weight      |       0xaccb9980 |        0x1810000 |
+|  247 | blk.27.attn_k.weight      |       0xae4c9980 |         0x1b8000 |
+|  248 | blk.27.attn_norm.weight   |       0xae681980 |           0x4000 |
+|  249 | blk.27.attn_output.weight |       0xae685980 |         0x6e0000 |
+|  250 | blk.27.attn_q.weight      |       0xaed65980 |         0x6e0000 |
+|  251 | blk.27.attn_v.weight      |       0xaf445980 |         0x1b8000 |
+|  252 | blk.27.ffn_down.weight    |       0xaf5fd980 |        0x1f80000 |
+|  253 | blk.27.ffn_gate.weight    |       0xb157d980 |        0x1810000 |
+|  254 | blk.27.ffn_norm.weight    |       0xb2d8d980 |           0x4000 |
+|  255 | blk.27.ffn_up.weight      |       0xb2d91980 |        0x1810000 |
+|  256 | blk.28.attn_k.weight      |       0xb45a1980 |         0x1b8000 |
+|  257 | blk.28.attn_norm.weight   |       0xb4759980 |           0x4000 |
+|  258 | blk.28.attn_output.weight |       0xb475d980 |         0x6e0000 |
+|  259 | blk.28.attn_q.weight      |       0xb4e3d980 |         0x6e0000 |
+|  260 | blk.28.attn_v.weight      |       0xb551d980 |         0x1b8000 |
+|  261 | blk.28.ffn_down.weight    |       0xb56d5980 |        0x1f80000 |
+|  262 | blk.28.ffn_gate.weight    |       0xb7655980 |        0x1810000 |
+|  263 | blk.28.ffn_norm.weight    |       0xb8e65980 |           0x4000 |
+|  264 | blk.28.ffn_up.weight      |       0xb8e69980 |        0x1810000 |
+|  265 | blk.29.attn_k.weight      |       0xba679980 |         0x1b8000 |
+|  266 | blk.29.attn_norm.weight   |       0xba831980 |           0x4000 |
+|  267 | blk.29.attn_output.weight |       0xba835980 |         0x6e0000 |
+|  268 | blk.29.attn_q.weight      |       0xbaf15980 |         0x6e0000 |
+|  269 | blk.29.attn_v.weight      |       0xbb5f5980 |         0x1b8000 |
+|  270 | blk.29.ffn_down.weight    |       0xbb7ad980 |        0x1f80000 |
+|  271 | blk.29.ffn_gate.weight    |       0xbd72d980 |        0x1810000 |
+|  272 | blk.29.ffn_norm.weight    |       0xbef3d980 |           0x4000 |
+|  273 | blk.29.ffn_up.weight      |       0xbef41980 |        0x1810000 |
+|  274 | blk.30.attn_k.weight      |       0xc0751980 |         0x1b8000 |
+|  275 | blk.30.attn_norm.weight   |       0xc0909980 |           0x4000 |
+|  276 | blk.30.attn_output.weight |       0xc090d980 |         0x6e0000 |
+|  277 | blk.30.attn_q.weight      |       0xc0fed980 |         0x6e0000 |
+|  278 | blk.30.attn_v.weight      |       0xc16cd980 |         0x1b8000 |
+|  279 | blk.30.ffn_down.weight    |       0xc1885980 |        0x1f80000 |
+|  280 | blk.30.ffn_gate.weight    |       0xc3805980 |        0x1810000 |
+|  281 | blk.30.ffn_norm.weight    |       0xc5015980 |           0x4000 |
+|  282 | blk.30.ffn_up.weight      |       0xc5019980 |        0x1810000 |
+|  283 | blk.31.attn_k.weight      |       0xc6829980 |         0x188000 |
+|  284 | blk.31.attn_norm.weight   |       0xc69b1980 |           0x4000 |
+|  285 | blk.31.attn_output.weight |       0xc69b5980 |         0x6e0000 |
+|  286 | blk.31.attn_q.weight      |       0xc7095980 |         0x620000 |
+|  287 | blk.31.attn_v.weight      |       0xc76b5980 |         0x1b8000 |
+|  288 | blk.31.ffn_down.weight    |       0xc786d980 |        0x1f80000 |
+|  289 | blk.31.ffn_gate.weight    |       0xc97ed980 |        0x1810000 |
+|  290 | blk.31.ffn_norm.weight    |       0xcaffd980 |           0x4000 |
+|  291 | blk.31.ffn_up.weight      |       0xcb001980 |        0x1810000 |
+### <a name="base">Base Tensor Group : ~1B Elements</a>
+| T_ID | Tensor Layer Name  | Human Friendly Tensor Layer Name | Elements          | Shape                 | Type    |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:--------|
+|    0 | output.weight      | Output (W)                       | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | IQ3_XXS |
+|    1 | output_norm.weight | Output Normalization (W)         | (  ~4K)      4096 | 4096 x      1 x 1 x 1 | F32     |
+|    2 | rope_freqs.weight  | Rope_Freqs (W)                   | (   64)        64 |   64 x      1 x 1 x 1 | F32     |
+|    3 | token_embd.weight  | Token Embedding (W)              | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | IQ3_XXS |
+- Total elements in base: ( ~1B) 1050677312
+- Percentage of total elements: 13.08%
+### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|    4 | blk.0.attn_k.weight      | Block 0 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|    5 | blk.0.attn_norm.weight   | Block 0 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|    6 | blk.0.attn_output.weight | Block 0 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|    7 | blk.0.attn_q.weight      | Block 0 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|    8 | blk.0.attn_v.weight      | Block 0 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|    9 | blk.0.ffn_down.weight    | Block 0 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|   10 | blk.0.ffn_gate.weight    | Block 0 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   11 | blk.0.ffn_norm.weight    | Block 0 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   12 | blk.0.ffn_up.weight      | Block 0 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.0: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   13 | blk.1.attn_k.weight      | Block 1 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   14 | blk.1.attn_norm.weight   | Block 1 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   15 | blk.1.attn_output.weight | Block 1 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|   16 | blk.1.attn_q.weight      | Block 1 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   17 | blk.1.attn_v.weight      | Block 1 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   18 | blk.1.ffn_down.weight    | Block 1 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|   19 | blk.1.ffn_gate.weight    | Block 1 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   20 | blk.1.ffn_norm.weight    | Block 1 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   21 | blk.1.ffn_up.weight      | Block 1 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.1: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   22 | blk.2.attn_k.weight      | Block 2 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   23 | blk.2.attn_norm.weight   | Block 2 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   24 | blk.2.attn_output.weight | Block 2 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|   25 | blk.2.attn_q.weight      | Block 2 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   26 | blk.2.attn_v.weight      | Block 2 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   27 | blk.2.ffn_down.weight    | Block 2 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|   28 | blk.2.ffn_gate.weight    | Block 2 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   29 | blk.2.ffn_norm.weight    | Block 2 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   30 | blk.2.ffn_up.weight      | Block 2 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.2: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   31 | blk.3.attn_k.weight      | Block 3 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   32 | blk.3.attn_norm.weight   | Block 3 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   33 | blk.3.attn_output.weight | Block 3 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|   34 | blk.3.attn_q.weight      | Block 3 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   35 | blk.3.attn_v.weight      | Block 3 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   36 | blk.3.ffn_down.weight    | Block 3 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|   37 | blk.3.ffn_gate.weight    | Block 3 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   38 | blk.3.ffn_norm.weight    | Block 3 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   39 | blk.3.ffn_up.weight      | Block 3 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.3: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   40 | blk.4.attn_k.weight      | Block 4 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   41 | blk.4.attn_norm.weight   | Block 4 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   42 | blk.4.attn_output.weight | Block 4 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|   43 | blk.4.attn_q.weight      | Block 4 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   44 | blk.4.attn_v.weight      | Block 4 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   45 | blk.4.ffn_down.weight    | Block 4 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|   46 | blk.4.ffn_gate.weight    | Block 4 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   47 | blk.4.ffn_norm.weight    | Block 4 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   48 | blk.4.ffn_up.weight      | Block 4 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.4: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   49 | blk.5.attn_k.weight      | Block 5 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   50 | blk.5.attn_norm.weight   | Block 5 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   51 | blk.5.attn_output.weight | Block 5 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|   52 | blk.5.attn_q.weight      | Block 5 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   53 | blk.5.attn_v.weight      | Block 5 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   54 | blk.5.ffn_down.weight    | Block 5 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|   55 | blk.5.ffn_gate.weight    | Block 5 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   56 | blk.5.ffn_norm.weight    | Block 5 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   57 | blk.5.ffn_up.weight      | Block 5 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.5: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   58 | blk.6.attn_k.weight      | Block 6 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   59 | blk.6.attn_norm.weight   | Block 6 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   60 | blk.6.attn_output.weight | Block 6 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|   61 | blk.6.attn_q.weight      | Block 6 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   62 | blk.6.attn_v.weight      | Block 6 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   63 | blk.6.ffn_down.weight    | Block 6 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|   64 | blk.6.ffn_gate.weight    | Block 6 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   65 | blk.6.ffn_norm.weight    | Block 6 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   66 | blk.6.ffn_up.weight      | Block 6 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.6: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   67 | blk.7.attn_k.weight      | Block 7 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   68 | blk.7.attn_norm.weight   | Block 7 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   69 | blk.7.attn_output.weight | Block 7 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|   70 | blk.7.attn_q.weight      | Block 7 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   71 | blk.7.attn_v.weight      | Block 7 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   72 | blk.7.ffn_down.weight    | Block 7 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|   73 | blk.7.ffn_gate.weight    | Block 7 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   74 | blk.7.ffn_norm.weight    | Block 7 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   75 | blk.7.ffn_up.weight      | Block 7 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.7: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   76 | blk.8.attn_k.weight      | Block 8 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   77 | blk.8.attn_norm.weight   | Block 8 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   78 | blk.8.attn_output.weight | Block 8 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|   79 | blk.8.attn_q.weight      | Block 8 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   80 | blk.8.attn_v.weight      | Block 8 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   81 | blk.8.ffn_down.weight    | Block 8 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|   82 | blk.8.ffn_gate.weight    | Block 8 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   83 | blk.8.ffn_norm.weight    | Block 8 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   84 | blk.8.ffn_up.weight      | Block 8 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.8: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type    |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:--------|
+|   85 | blk.9.attn_k.weight      | Block 9 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   86 | blk.9.attn_norm.weight   | Block 9 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   87 | blk.9.attn_output.weight | Block 9 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|   88 | blk.9.attn_q.weight      | Block 9 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   89 | blk.9.attn_v.weight      | Block 9 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   90 | blk.9.ffn_down.weight    | Block 9 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|   91 | blk.9.ffn_gate.weight    | Block 9 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|   92 | blk.9.ffn_norm.weight    | Block 9 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   93 | blk.9.ffn_up.weight      | Block 9 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.9: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|   94 | blk.10.attn_k.weight      | Block 10 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|   95 | blk.10.attn_norm.weight   | Block 10 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|   96 | blk.10.attn_output.weight | Block 10 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|   97 | blk.10.attn_q.weight      | Block 10 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|   98 | blk.10.attn_v.weight      | Block 10 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|   99 | blk.10.ffn_down.weight    | Block 10 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|  100 | blk.10.ffn_gate.weight    | Block 10 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|  101 | blk.10.ffn_norm.weight    | Block 10 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  102 | blk.10.ffn_up.weight      | Block 10 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.10: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  103 | blk.11.attn_k.weight      | Block 11 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|  104 | blk.11.attn_norm.weight   | Block 11 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  105 | blk.11.attn_output.weight | Block 11 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|  106 | blk.11.attn_q.weight      | Block 11 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|  107 | blk.11.attn_v.weight      | Block 11 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  108 | blk.11.ffn_down.weight    | Block 11 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|  109 | blk.11.ffn_gate.weight    | Block 11 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|  110 | blk.11.ffn_norm.weight    | Block 11 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  111 | blk.11.ffn_up.weight      | Block 11 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.11: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  112 | blk.12.attn_k.weight      | Block 12 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|  113 | blk.12.attn_norm.weight   | Block 12 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  114 | blk.12.attn_output.weight | Block 12 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|  115 | blk.12.attn_q.weight      | Block 12 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|  116 | blk.12.attn_v.weight      | Block 12 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  117 | blk.12.ffn_down.weight    | Block 12 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|  118 | blk.12.ffn_gate.weight    | Block 12 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|  119 | blk.12.ffn_norm.weight    | Block 12 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  120 | blk.12.ffn_up.weight      | Block 12 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.12: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  121 | blk.13.attn_k.weight      | Block 13 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  122 | blk.13.attn_norm.weight   | Block 13 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  123 | blk.13.attn_output.weight | Block 13 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|  124 | blk.13.attn_q.weight      | Block 13 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|  125 | blk.13.attn_v.weight      | Block 13 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  126 | blk.13.ffn_down.weight    | Block 13 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|  127 | blk.13.ffn_gate.weight    | Block 13 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|  128 | blk.13.ffn_norm.weight    | Block 13 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  129 | blk.13.ffn_up.weight      | Block 13 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.13: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  130 | blk.14.attn_k.weight      | Block 14 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  131 | blk.14.attn_norm.weight   | Block 14 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  132 | blk.14.attn_output.weight | Block 14 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|  133 | blk.14.attn_q.weight      | Block 14 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|  134 | blk.14.attn_v.weight      | Block 14 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  135 | blk.14.ffn_down.weight    | Block 14 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|  136 | blk.14.ffn_gate.weight    | Block 14 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|  137 | blk.14.ffn_norm.weight    | Block 14 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  138 | blk.14.ffn_up.weight      | Block 14 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.14: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  139 | blk.15.attn_k.weight      | Block 15 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|  140 | blk.15.attn_norm.weight   | Block 15 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  141 | blk.15.attn_output.weight | Block 15 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|  142 | blk.15.attn_q.weight      | Block 15 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|  143 | blk.15.attn_v.weight      | Block 15 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  144 | blk.15.ffn_down.weight    | Block 15 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S   |
+|  145 | blk.15.ffn_gate.weight    | Block 15 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+|  146 | blk.15.ffn_norm.weight    | Block 15 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  147 | blk.15.ffn_up.weight      | Block 15 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_XXS |
+- Total elements in blk.15: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type  |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:------|
+|  148 | blk.16.attn_k.weight      | Block 16 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S |
+|  149 | blk.16.attn_norm.weight   | Block 16 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32   |
+|  150 | blk.16.attn_output.weight | Block 16 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S |
+|  151 | blk.16.attn_q.weight      | Block 16 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S |
+|  152 | blk.16.attn_v.weight      | Block 16 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S |
+|  153 | blk.16.ffn_down.weight    | Block 16 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ3_S |
+|  154 | blk.16.ffn_gate.weight    | Block 16 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S |
+|  155 | blk.16.ffn_norm.weight    | Block 16 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32   |
+|  156 | blk.16.ffn_up.weight      | Block 16 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S |
+- Total elements in blk.16: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  157 | blk.17.attn_k.weight      | Block 17 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|  158 | blk.17.attn_norm.weight   | Block 17 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  159 | blk.17.attn_output.weight | Block 17 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|  160 | blk.17.attn_q.weight      | Block 17 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|  161 | blk.17.attn_v.weight      | Block 17 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  162 | blk.17.ffn_down.weight    | Block 17 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|  163 | blk.17.ffn_gate.weight    | Block 17 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S   |
+|  164 | blk.17.ffn_norm.weight    | Block 17 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  165 | blk.17.ffn_up.weight      | Block 17 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S   |
+- Total elements in blk.17: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  166 | blk.18.attn_k.weight      | Block 18 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  167 | blk.18.attn_norm.weight   | Block 18 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  168 | blk.18.attn_output.weight | Block 18 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  169 | blk.18.attn_q.weight      | Block 18 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  170 | blk.18.attn_v.weight      | Block 18 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  171 | blk.18.ffn_down.weight    | Block 18 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  172 | blk.18.ffn_gate.weight    | Block 18 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  173 | blk.18.ffn_norm.weight    | Block 18 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  174 | blk.18.ffn_up.weight      | Block 18 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.18: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  175 | blk.19.attn_k.weight      | Block 19 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  176 | blk.19.attn_norm.weight   | Block 19 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  177 | blk.19.attn_output.weight | Block 19 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  178 | blk.19.attn_q.weight      | Block 19 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  179 | blk.19.attn_v.weight      | Block 19 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  180 | blk.19.ffn_down.weight    | Block 19 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  181 | blk.19.ffn_gate.weight    | Block 19 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  182 | blk.19.ffn_norm.weight    | Block 19 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  183 | blk.19.ffn_up.weight      | Block 19 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.19: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  184 | blk.20.attn_k.weight      | Block 20 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  185 | blk.20.attn_norm.weight   | Block 20 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  186 | blk.20.attn_output.weight | Block 20 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  187 | blk.20.attn_q.weight      | Block 20 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  188 | blk.20.attn_v.weight      | Block 20 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  189 | blk.20.ffn_down.weight    | Block 20 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  190 | blk.20.ffn_gate.weight    | Block 20 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  191 | blk.20.ffn_norm.weight    | Block 20 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  192 | blk.20.ffn_up.weight      | Block 20 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.20: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  193 | blk.21.attn_k.weight      | Block 21 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  194 | blk.21.attn_norm.weight   | Block 21 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  195 | blk.21.attn_output.weight | Block 21 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  196 | blk.21.attn_q.weight      | Block 21 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  197 | blk.21.attn_v.weight      | Block 21 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  198 | blk.21.ffn_down.weight    | Block 21 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  199 | blk.21.ffn_gate.weight    | Block 21 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  200 | blk.21.ffn_norm.weight    | Block 21 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  201 | blk.21.ffn_up.weight      | Block 21 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.21: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  202 | blk.22.attn_k.weight      | Block 22 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  203 | blk.22.attn_norm.weight   | Block 22 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  204 | blk.22.attn_output.weight | Block 22 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  205 | blk.22.attn_q.weight      | Block 22 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  206 | blk.22.attn_v.weight      | Block 22 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  207 | blk.22.ffn_down.weight    | Block 22 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  208 | blk.22.ffn_gate.weight    | Block 22 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  209 | blk.22.ffn_norm.weight    | Block 22 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  210 | blk.22.ffn_up.weight      | Block 22 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.22: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  211 | blk.23.attn_k.weight      | Block 23 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  212 | blk.23.attn_norm.weight   | Block 23 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  213 | blk.23.attn_output.weight | Block 23 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  214 | blk.23.attn_q.weight      | Block 23 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  215 | blk.23.attn_v.weight      | Block 23 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  216 | blk.23.ffn_down.weight    | Block 23 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  217 | blk.23.ffn_gate.weight    | Block 23 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  218 | blk.23.ffn_norm.weight    | Block 23 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  219 | blk.23.ffn_up.weight      | Block 23 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.23: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  220 | blk.24.attn_k.weight      | Block 24 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  221 | blk.24.attn_norm.weight   | Block 24 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  222 | blk.24.attn_output.weight | Block 24 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  223 | blk.24.attn_q.weight      | Block 24 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  224 | blk.24.attn_v.weight      | Block 24 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  225 | blk.24.ffn_down.weight    | Block 24 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  226 | blk.24.ffn_gate.weight    | Block 24 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  227 | blk.24.ffn_norm.weight    | Block 24 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  228 | blk.24.ffn_up.weight      | Block 24 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.24: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  229 | blk.25.attn_k.weight      | Block 25 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  230 | blk.25.attn_norm.weight   | Block 25 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  231 | blk.25.attn_output.weight | Block 25 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  232 | blk.25.attn_q.weight      | Block 25 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  233 | blk.25.attn_v.weight      | Block 25 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  234 | blk.25.ffn_down.weight    | Block 25 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  235 | blk.25.ffn_gate.weight    | Block 25 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  236 | blk.25.ffn_norm.weight    | Block 25 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  237 | blk.25.ffn_up.weight      | Block 25 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.25: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  238 | blk.26.attn_k.weight      | Block 26 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  239 | blk.26.attn_norm.weight   | Block 26 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  240 | blk.26.attn_output.weight | Block 26 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  241 | blk.26.attn_q.weight      | Block 26 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  242 | blk.26.attn_v.weight      | Block 26 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  243 | blk.26.ffn_down.weight    | Block 26 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  244 | blk.26.ffn_gate.weight    | Block 26 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  245 | blk.26.ffn_norm.weight    | Block 26 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  246 | blk.26.ffn_up.weight      | Block 26 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.26: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  247 | blk.27.attn_k.weight      | Block 27 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  248 | blk.27.attn_norm.weight   | Block 27 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  249 | blk.27.attn_output.weight | Block 27 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  250 | blk.27.attn_q.weight      | Block 27 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  251 | blk.27.attn_v.weight      | Block 27 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  252 | blk.27.ffn_down.weight    | Block 27 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  253 | blk.27.ffn_gate.weight    | Block 27 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  254 | blk.27.ffn_norm.weight    | Block 27 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  255 | blk.27.ffn_up.weight      | Block 27 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.27: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  256 | blk.28.attn_k.weight      | Block 28 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  257 | blk.28.attn_norm.weight   | Block 28 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  258 | blk.28.attn_output.weight | Block 28 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  259 | blk.28.attn_q.weight      | Block 28 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  260 | blk.28.attn_v.weight      | Block 28 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  261 | blk.28.ffn_down.weight    | Block 28 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  262 | blk.28.ffn_gate.weight    | Block 28 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  263 | blk.28.ffn_norm.weight    | Block 28 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  264 | blk.28.ffn_up.weight      | Block 28 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.28: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  265 | blk.29.attn_k.weight      | Block 29 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  266 | blk.29.attn_norm.weight   | Block 29 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  267 | blk.29.attn_output.weight | Block 29 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  268 | blk.29.attn_q.weight      | Block 29 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  269 | blk.29.attn_v.weight      | Block 29 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  270 | blk.29.ffn_down.weight    | Block 29 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  271 | blk.29.ffn_gate.weight    | Block 29 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  272 | blk.29.ffn_norm.weight    | Block 29 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  273 | blk.29.ffn_up.weight      | Block 29 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.29: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  274 | blk.30.attn_k.weight      | Block 30 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  275 | blk.30.attn_norm.weight   | Block 30 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  276 | blk.30.attn_output.weight | Block 30 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  277 | blk.30.attn_q.weight      | Block 30 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  278 | blk.30.attn_v.weight      | Block 30 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  279 | blk.30.ffn_down.weight    | Block 30 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL |
+|  280 | blk.30.ffn_gate.weight    | Block 30 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  281 | blk.30.ffn_norm.weight    | Block 30 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  282 | blk.30.ffn_up.weight      | Block 30 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.30: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type    |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:--------|
+|  283 | blk.31.attn_k.weight      | Block 31 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_XXS |
+|  284 | blk.31.attn_norm.weight   | Block 31 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  285 | blk.31.attn_output.weight | Block 31 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S   |
+|  286 | blk.31.attn_q.weight      | Block 31 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_XXS |
+|  287 | blk.31.attn_v.weight      | Block 31 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S   |
+|  288 | blk.31.ffn_down.weight    | Block 31 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | IQ4_NL  |
+|  289 | blk.31.ffn_gate.weight    | Block 31 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S   |
+|  290 | blk.31.ffn_norm.weight    | Block 31 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32     |
+|  291 | blk.31.ffn_up.weight      | Block 31 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S   |
+- Total elements in blk.31: (~218M) 218112000
+- Percentage of total elements: 2.72%

scores/Llama-Guard-3-8B-IQ4_NL.md ADDED Viewed

	@@ -0,0 +1,978 @@

+# Llama-Guard-3-8B-IQ4_NL.gguf - GGUF Internal File Dump
+- Endian: LITTLE endian
+## Key Value Metadata Store
+There are 39 key-value pairs in this file
+| POS | TYPE     |  Count | Key                                    | Value                                                               |
+|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
+|   1 | UINT32   |      1 | GGUF.version                           | 3                                                                   |
+|   2 | UINT64   |      1 | GGUF.tensor_count                      | 292                                                                 |
+|   3 | UINT64   |      1 | GGUF.kv_count                          | 36                                                                  |
+|   4 | STRING   |      1 | general.architecture                   | `llama`                                                             |
+|   5 | STRING   |      1 | general.type                           | `model`                                                             |
+|   6 | STRING   |      1 | general.name                           | `Llama Guard 3 8B`                                                  |
+|   7 | STRING   |      1 | general.basename                       | `Llama-Guard-3`                                                     |
+|   8 | STRING   |      1 | general.size_label                     | `8B`                                                                |
+|   9 | STRING   |      1 | general.license                        | `llama3.1`                                                          |
+|  10 | UINT32   |      1 | general.base_model.count               | 1                                                                   |
+|  11 | STRING   |      1 | general.base_model.0.name              | `Meta Llama 3.1 8B`                                                 |
+|  12 | STRING   |      1 | general.base_model.0.organization      | `Meta Llama`                                                        |
+|  13 | STRING   |      1 | general.base_model.0.repo_url          | `https://huggingface.co/meta-llama/Meta-Llama-3.1-8B`               |
+|  14 | [STRING] |      6 | general.tags                           | [ `facebook`, `meta`, `pytorch`, `llama`, `llama-3`, ... ]          |
+|  15 | [STRING] |      1 | general.languages                      | [ `en` ]                                                            |
+|  16 | UINT32   |      1 | llama.block_count                      | 32                                                                  |
+|  17 | UINT32   |      1 | llama.context_length                   | 131072                                                              |
+|  18 | UINT32   |      1 | llama.embedding_length                 | 4096                                                                |
+|  19 | UINT32   |      1 | llama.feed_forward_length              | 14336                                                               |
+|  20 | UINT32   |      1 | llama.attention.head_count             | 32                                                                  |
+|  21 | UINT32   |      1 | llama.attention.head_count_kv          | 8                                                                   |
+|  22 | FLOAT32  |      1 | llama.rope.freq_base                   | 500000.0                                                            |
+|  23 | FLOAT32  |      1 | llama.attention.layer_norm_rms_epsilon | 1e-05                                                               |
+|  24 | UINT32   |      1 | llama.vocab_size                       | 128256                                                              |
+|  25 | UINT32   |      1 | llama.rope.dimension_count             | 128                                                                 |
+|  26 | STRING   |      1 | tokenizer.ggml.model                   | `gpt2`                                                              |
+|  27 | STRING   |      1 | tokenizer.ggml.pre                     | `smaug-bpe`                                                         |
+|  28 | [STRING] | 128256 | tokenizer.ggml.tokens                  | [ `!`, `"`, `#`, `$`, `%`, ... ]                                    |
+|  29 | [INT32]  | 128256 | tokenizer.ggml.token_type              | [ 1, 1, 1, 1, 1, 1, 1, ... ]                                        |
+|  30 | [STRING] | 280147 | tokenizer.ggml.merges                  | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]                    |
+|  31 | UINT32   |      1 | tokenizer.ggml.bos_token_id            | 128000                                                              |
+|  32 | UINT32   |      1 | tokenizer.ggml.eos_token_id            | 128009                                                              |
+|  33 | STRING   |      1 | tokenizer.chat_template                | `{% if messages|length % 2 == 0`...`assistant<|end_header_id|>" }}` |
+|  34 | UINT32   |      1 | general.quantization_version           | 2                                                                   |
+|  35 | UINT32   |      1 | general.file_type                      | 25                                                                  |
+|  36 | STRING   |      1 | quantize.imatrix.file                  | `./imatrix/imatrix-Llama-Guard-3-8B-small.dat`                      |
+|  37 | STRING   |      1 | quantize.imatrix.dataset               | `../../datasets/imatrix/calibration_eur_small.txt`                  |
+|  38 | INT32    |      1 | quantize.imatrix.entries_count         | 224                                                                 |
+|  39 | INT32    |      1 | quantize.imatrix.chunks_count          | 962                                                                 |
+## Tensors Overview ~8B Elements
+Total number of elements in all tensors: 8030261312 Elements
+- [Llama-Guard-3-8B-IQ4\_NL.gguf - GGUF Internal File Dump](#llama-guard-3-8b-iq4_nlgguf---gguf-internal-file-dump)
+  - [Key Value Metadata Store](#key-value-metadata-store)
+  - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
+    - [Tensor Data Offset](#tensor-data-offset)
+    - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
+    - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
+    - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
+    - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
+    - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
+    - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
+    - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
+    - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
+    - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
+    - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
+    - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
+    - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
+    - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
+    - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
+    - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
+    - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
+    - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
+    - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
+    - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
+    - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
+    - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
+    - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
+    - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
+    - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
+    - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
+    - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
+    - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
+    - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
+    - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
+    - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
+    - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
+    - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
+    - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
+### Tensor Data Offset
+This table contains the offset and data segment relative to start of file
+| T_ID | Tensor Layer Name         |  Data Offset (B) |    Data Size (B) |
+|-----:|:--------------------------|-----------------:|-----------------:|
+|    0 | output.weight             |         0x779880 |       0x119d0000 |
+|    1 | output_norm.weight        |       0x12149880 |           0x4000 |
+|    2 | rope_freqs.weight         |       0x1214d880 |            0x100 |
+|    3 | token_embd.weight         |       0x1214d980 |        0xd746000 |
+|    4 | blk.0.attn_k.weight       |       0x1f893980 |         0x1b8000 |
+|    5 | blk.0.attn_norm.weight    |       0x1fa4b980 |           0x4000 |
+|    6 | blk.0.attn_output.weight  |       0x1fa4f980 |         0x900000 |
+|    7 | blk.0.attn_q.weight       |       0x2034f980 |         0x6e0000 |
+|    8 | blk.0.attn_v.weight       |       0x20a2f980 |         0x220000 |
+|    9 | blk.0.ffn_down.weight     |       0x20c4f980 |        0x2680000 |
+|   10 | blk.0.ffn_gate.weight     |       0x232cf980 |        0x1810000 |
+|   11 | blk.0.ffn_norm.weight     |       0x24adf980 |           0x4000 |
+|   12 | blk.0.ffn_up.weight       |       0x24ae3980 |        0x1810000 |
+|   13 | blk.1.attn_k.weight       |       0x262f3980 |         0x1b8000 |
+|   14 | blk.1.attn_norm.weight    |       0x264ab980 |           0x4000 |
+|   15 | blk.1.attn_output.weight  |       0x264af980 |         0x900000 |
+|   16 | blk.1.attn_q.weight       |       0x26daf980 |         0x6e0000 |
+|   17 | blk.1.attn_v.weight       |       0x2748f980 |         0x220000 |
+|   18 | blk.1.ffn_down.weight     |       0x276af980 |        0x2680000 |
+|   19 | blk.1.ffn_gate.weight     |       0x29d2f980 |        0x1810000 |
+|   20 | blk.1.ffn_norm.weight     |       0x2b53f980 |           0x4000 |
+|   21 | blk.1.ffn_up.weight       |       0x2b543980 |        0x1810000 |
+|   22 | blk.2.attn_k.weight       |       0x2cd53980 |         0x1b8000 |
+|   23 | blk.2.attn_norm.weight    |       0x2cf0b980 |           0x4000 |
+|   24 | blk.2.attn_output.weight  |       0x2cf0f980 |         0x900000 |
+|   25 | blk.2.attn_q.weight       |       0x2d80f980 |         0x6e0000 |
+|   26 | blk.2.attn_v.weight       |       0x2deef980 |         0x220000 |
+|   27 | blk.2.ffn_down.weight     |       0x2e10f980 |        0x2680000 |
+|   28 | blk.2.ffn_gate.weight     |       0x3078f980 |        0x1810000 |
+|   29 | blk.2.ffn_norm.weight     |       0x31f9f980 |           0x4000 |
+|   30 | blk.2.ffn_up.weight       |       0x31fa3980 |        0x1810000 |
+|   31 | blk.3.attn_k.weight       |       0x337b3980 |         0x1b8000 |
+|   32 | blk.3.attn_norm.weight    |       0x3396b980 |           0x4000 |
+|   33 | blk.3.attn_output.weight  |       0x3396f980 |         0x900000 |
+|   34 | blk.3.attn_q.weight       |       0x3426f980 |         0x6e0000 |
+|   35 | blk.3.attn_v.weight       |       0x3494f980 |         0x220000 |
+|   36 | blk.3.ffn_down.weight     |       0x34b6f980 |        0x2680000 |
+|   37 | blk.3.ffn_gate.weight     |       0x371ef980 |        0x1810000 |
+|   38 | blk.3.ffn_norm.weight     |       0x389ff980 |           0x4000 |
+|   39 | blk.3.ffn_up.weight       |       0x38a03980 |        0x1810000 |
+|   40 | blk.4.attn_k.weight       |       0x3a213980 |         0x1b8000 |
+|   41 | blk.4.attn_norm.weight    |       0x3a3cb980 |           0x4000 |
+|   42 | blk.4.attn_output.weight  |       0x3a3cf980 |         0x900000 |
+|   43 | blk.4.attn_q.weight       |       0x3accf980 |         0x6e0000 |
+|   44 | blk.4.attn_v.weight       |       0x3b3af980 |         0x220000 |
+|   45 | blk.4.ffn_down.weight     |       0x3b5cf980 |        0x2680000 |
+|   46 | blk.4.ffn_gate.weight     |       0x3dc4f980 |        0x1810000 |
+|   47 | blk.4.ffn_norm.weight     |       0x3f45f980 |           0x4000 |
+|   48 | blk.4.ffn_up.weight       |       0x3f463980 |        0x1810000 |
+|   49 | blk.5.attn_k.weight       |       0x40c73980 |         0x1b8000 |
+|   50 | blk.5.attn_norm.weight    |       0x40e2b980 |           0x4000 |
+|   51 | blk.5.attn_output.weight  |       0x40e2f980 |         0x900000 |
+|   52 | blk.5.attn_q.weight       |       0x4172f980 |         0x6e0000 |
+|   53 | blk.5.attn_v.weight       |       0x41e0f980 |         0x220000 |
+|   54 | blk.5.ffn_down.weight     |       0x4202f980 |        0x2680000 |
+|   55 | blk.5.ffn_gate.weight     |       0x446af980 |        0x1810000 |
+|   56 | blk.5.ffn_norm.weight     |       0x45ebf980 |           0x4000 |
+|   57 | blk.5.ffn_up.weight       |       0x45ec3980 |        0x1810000 |
+|   58 | blk.6.attn_k.weight       |       0x476d3980 |         0x1b8000 |
+|   59 | blk.6.attn_norm.weight    |       0x4788b980 |           0x4000 |
+|   60 | blk.6.attn_output.weight  |       0x4788f980 |         0x900000 |
+|   61 | blk.6.attn_q.weight       |       0x4818f980 |         0x6e0000 |
+|   62 | blk.6.attn_v.weight       |       0x4886f980 |         0x220000 |
+|   63 | blk.6.ffn_down.weight     |       0x48a8f980 |        0x2680000 |
+|   64 | blk.6.ffn_gate.weight     |       0x4b10f980 |        0x1810000 |
+|   65 | blk.6.ffn_norm.weight     |       0x4c91f980 |           0x4000 |
+|   66 | blk.6.ffn_up.weight       |       0x4c923980 |        0x1810000 |
+|   67 | blk.7.attn_k.weight       |       0x4e133980 |         0x1b8000 |
+|   68 | blk.7.attn_norm.weight    |       0x4e2eb980 |           0x4000 |
+|   69 | blk.7.attn_output.weight  |       0x4e2ef980 |         0x900000 |
+|   70 | blk.7.attn_q.weight       |       0x4ebef980 |         0x6e0000 |
+|   71 | blk.7.attn_v.weight       |       0x4f2cf980 |         0x220000 |
+|   72 | blk.7.ffn_down.weight     |       0x4f4ef980 |        0x2680000 |
+|   73 | blk.7.ffn_gate.weight     |       0x51b6f980 |        0x1810000 |
+|   74 | blk.7.ffn_norm.weight     |       0x5337f980 |           0x4000 |
+|   75 | blk.7.ffn_up.weight       |       0x53383980 |        0x1810000 |
+|   76 | blk.8.attn_k.weight       |       0x54b93980 |         0x1b8000 |
+|   77 | blk.8.attn_norm.weight    |       0x54d4b980 |           0x4000 |
+|   78 | blk.8.attn_output.weight  |       0x54d4f980 |         0x900000 |
+|   79 | blk.8.attn_q.weight       |       0x5564f980 |         0x6e0000 |
+|   80 | blk.8.attn_v.weight       |       0x55d2f980 |         0x220000 |
+|   81 | blk.8.ffn_down.weight     |       0x55f4f980 |        0x2680000 |
+|   82 | blk.8.ffn_gate.weight     |       0x585cf980 |        0x1810000 |
+|   83 | blk.8.ffn_norm.weight     |       0x59ddf980 |           0x4000 |
+|   84 | blk.8.ffn_up.weight       |       0x59de3980 |        0x1810000 |
+|   85 | blk.9.attn_k.weight       |       0x5b5f3980 |         0x1b8000 |
+|   86 | blk.9.attn_norm.weight    |       0x5b7ab980 |           0x4000 |
+|   87 | blk.9.attn_output.weight  |       0x5b7af980 |         0x900000 |
+|   88 | blk.9.attn_q.weight       |       0x5c0af980 |         0x6e0000 |
+|   89 | blk.9.attn_v.weight       |       0x5c78f980 |         0x220000 |
+|   90 | blk.9.ffn_down.weight     |       0x5c9af980 |        0x2680000 |
+|   91 | blk.9.ffn_gate.weight     |       0x5f02f980 |        0x1810000 |
+|   92 | blk.9.ffn_norm.weight     |       0x6083f980 |           0x4000 |
+|   93 | blk.9.ffn_up.weight       |       0x60843980 |        0x1810000 |
+|   94 | blk.10.attn_k.weight      |       0x62053980 |         0x1b8000 |
+|   95 | blk.10.attn_norm.weight   |       0x6220b980 |           0x4000 |
+|   96 | blk.10.attn_output.weight |       0x6220f980 |         0x900000 |
+|   97 | blk.10.attn_q.weight      |       0x62b0f980 |         0x6e0000 |
+|   98 | blk.10.attn_v.weight      |       0x631ef980 |         0x220000 |
+|   99 | blk.10.ffn_down.weight    |       0x6340f980 |        0x2680000 |
+|  100 | blk.10.ffn_gate.weight    |       0x65a8f980 |        0x1810000 |
+|  101 | blk.10.ffn_norm.weight    |       0x6729f980 |           0x4000 |
+|  102 | blk.10.ffn_up.weight      |       0x672a3980 |        0x1810000 |
+|  103 | blk.11.attn_k.weight      |       0x68ab3980 |         0x1b8000 |
+|  104 | blk.11.attn_norm.weight   |       0x68c6b980 |           0x4000 |
+|  105 | blk.11.attn_output.weight |       0x68c6f980 |         0x900000 |
+|  106 | blk.11.attn_q.weight      |       0x6956f980 |         0x6e0000 |
+|  107 | blk.11.attn_v.weight      |       0x69c4f980 |         0x220000 |
+|  108 | blk.11.ffn_down.weight    |       0x69e6f980 |        0x2680000 |
+|  109 | blk.11.ffn_gate.weight    |       0x6c4ef980 |        0x1810000 |
+|  110 | blk.11.ffn_norm.weight    |       0x6dcff980 |           0x4000 |
+|  111 | blk.11.ffn_up.weight      |       0x6dd03980 |        0x1810000 |
+|  112 | blk.12.attn_k.weight      |       0x6f513980 |         0x1b8000 |
+|  113 | blk.12.attn_norm.weight   |       0x6f6cb980 |           0x4000 |
+|  114 | blk.12.attn_output.weight |       0x6f6cf980 |         0x900000 |
+|  115 | blk.12.attn_q.weight      |       0x6ffcf980 |         0x6e0000 |
+|  116 | blk.12.attn_v.weight      |       0x706af980 |         0x220000 |
+|  117 | blk.12.ffn_down.weight    |       0x708cf980 |        0x2680000 |
+|  118 | blk.12.ffn_gate.weight    |       0x72f4f980 |        0x1810000 |
+|  119 | blk.12.ffn_norm.weight    |       0x7475f980 |           0x4000 |
+|  120 | blk.12.ffn_up.weight      |       0x74763980 |        0x1810000 |
+|  121 | blk.13.attn_k.weight      |       0x75f73980 |         0x240000 |
+|  122 | blk.13.attn_norm.weight   |       0x761b3980 |           0x4000 |
+|  123 | blk.13.attn_output.weight |       0x761b7980 |         0x900000 |
+|  124 | blk.13.attn_q.weight      |       0x76ab7980 |         0x900000 |
+|  125 | blk.13.attn_v.weight      |       0x773b7980 |         0x240000 |
+|  126 | blk.13.ffn_down.weight    |       0x775f7980 |        0x2680000 |
+|  127 | blk.13.ffn_gate.weight    |       0x79c77980 |        0x1810000 |
+|  128 | blk.13.ffn_norm.weight    |       0x7b487980 |           0x4000 |
+|  129 | blk.13.ffn_up.weight      |       0x7b48b980 |        0x1810000 |
+|  130 | blk.14.attn_k.weight      |       0x7cc9b980 |         0x240000 |
+|  131 | blk.14.attn_norm.weight   |       0x7cedb980 |           0x4000 |
+|  132 | blk.14.attn_output.weight |       0x7cedf980 |         0x900000 |
+|  133 | blk.14.attn_q.weight      |       0x7d7df980 |         0x900000 |
+|  134 | blk.14.attn_v.weight      |       0x7e0df980 |         0x240000 |
+|  135 | blk.14.ffn_down.weight    |       0x7e31f980 |        0x2680000 |
+|  136 | blk.14.ffn_gate.weight    |       0x8099f980 |        0x1810000 |
+|  137 | blk.14.ffn_norm.weight    |       0x821af980 |           0x4000 |
+|  138 | blk.14.ffn_up.weight      |       0x821b3980 |        0x1810000 |
+|  139 | blk.15.attn_k.weight      |       0x839c3980 |         0x1b8000 |
+|  140 | blk.15.attn_norm.weight   |       0x83b7b980 |           0x4000 |
+|  141 | blk.15.attn_output.weight |       0x83b7f980 |         0x900000 |
+|  142 | blk.15.attn_q.weight      |       0x8447f980 |         0x6e0000 |
+|  143 | blk.15.attn_v.weight      |       0x84b5f980 |         0x220000 |
+|  144 | blk.15.ffn_down.weight    |       0x84d7f980 |        0x2680000 |
+|  145 | blk.15.ffn_gate.weight    |       0x873ff980 |        0x1810000 |
+|  146 | blk.15.ffn_norm.weight    |       0x88c0f980 |           0x4000 |
+|  147 | blk.15.ffn_up.weight      |       0x88c13980 |        0x1810000 |
+|  148 | blk.16.attn_k.weight      |       0x8a423980 |         0x240000 |
+|  149 | blk.16.attn_norm.weight   |       0x8a663980 |           0x4000 |
+|  150 | blk.16.attn_output.weight |       0x8a667980 |         0x900000 |
+|  151 | blk.16.attn_q.weight      |       0x8af67980 |         0x900000 |
+|  152 | blk.16.attn_v.weight      |       0x8b867980 |         0x240000 |
+|  153 | blk.16.ffn_down.weight    |       0x8baa7980 |        0x2680000 |
+|  154 | blk.16.ffn_gate.weight    |       0x8e127980 |        0x1f80000 |
+|  155 | blk.16.ffn_norm.weight    |       0x900a7980 |           0x4000 |
+|  156 | blk.16.ffn_up.weight      |       0x900ab980 |        0x1f80000 |
+|  157 | blk.17.attn_k.weight      |       0x9202b980 |         0x1b8000 |
+|  158 | blk.17.attn_norm.weight   |       0x921e3980 |           0x4000 |
+|  159 | blk.17.attn_output.weight |       0x921e7980 |         0x900000 |
+|  160 | blk.17.attn_q.weight      |       0x92ae7980 |         0x6e0000 |
+|  161 | blk.17.attn_v.weight      |       0x931c7980 |         0x220000 |
+|  162 | blk.17.ffn_down.weight    |       0x933e7980 |        0x2680000 |
+|  163 | blk.17.ffn_gate.weight    |       0x95a67980 |        0x1f80000 |
+|  164 | blk.17.ffn_norm.weight    |       0x979e7980 |           0x4000 |
+|  165 | blk.17.ffn_up.weight      |       0x979eb980 |        0x1f80000 |
+|  166 | blk.18.attn_k.weight      |       0x9996b980 |         0x240000 |
+|  167 | blk.18.attn_norm.weight   |       0x99bab980 |           0x4000 |
+|  168 | blk.18.attn_output.weight |       0x99baf980 |         0x900000 |
+|  169 | blk.18.attn_q.weight      |       0x9a4af980 |         0x900000 |
+|  170 | blk.18.attn_v.weight      |       0x9adaf980 |         0x240000 |
+|  171 | blk.18.ffn_down.weight    |       0x9afef980 |        0x2680000 |
+|  172 | blk.18.ffn_gate.weight    |       0x9d66f980 |        0x1f80000 |
+|  173 | blk.18.ffn_norm.weight    |       0x9f5ef980 |           0x4000 |
+|  174 | blk.18.ffn_up.weight      |       0x9f5f3980 |        0x1f80000 |
+|  175 | blk.19.attn_k.weight      |       0xa1573980 |         0x240000 |
+|  176 | blk.19.attn_norm.weight   |       0xa17b3980 |           0x4000 |
+|  177 | blk.19.attn_output.weight |       0xa17b7980 |         0x900000 |
+|  178 | blk.19.attn_q.weight      |       0xa20b7980 |         0x900000 |
+|  179 | blk.19.attn_v.weight      |       0xa29b7980 |         0x240000 |
+|  180 | blk.19.ffn_down.weight    |       0xa2bf7980 |        0x2680000 |
+|  181 | blk.19.ffn_gate.weight    |       0xa5277980 |        0x1f80000 |
+|  182 | blk.19.ffn_norm.weight    |       0xa71f7980 |           0x4000 |
+|  183 | blk.19.ffn_up.weight      |       0xa71fb980 |        0x1f80000 |
+|  184 | blk.20.attn_k.weight      |       0xa917b980 |         0x240000 |
+|  185 | blk.20.attn_norm.weight   |       0xa93bb980 |           0x4000 |
+|  186 | blk.20.attn_output.weight |       0xa93bf980 |         0x900000 |
+|  187 | blk.20.attn_q.weight      |       0xa9cbf980 |         0x900000 |
+|  188 | blk.20.attn_v.weight      |       0xaa5bf980 |         0x240000 |
+|  189 | blk.20.ffn_down.weight    |       0xaa7ff980 |        0x2680000 |
+|  190 | blk.20.ffn_gate.weight    |       0xace7f980 |        0x1f80000 |
+|  191 | blk.20.ffn_norm.weight    |       0xaedff980 |           0x4000 |
+|  192 | blk.20.ffn_up.weight      |       0xaee03980 |        0x1f80000 |
+|  193 | blk.21.attn_k.weight      |       0xb0d83980 |         0x240000 |
+|  194 | blk.21.attn_norm.weight   |       0xb0fc3980 |           0x4000 |
+|  195 | blk.21.attn_output.weight |       0xb0fc7980 |         0x900000 |
+|  196 | blk.21.attn_q.weight      |       0xb18c7980 |         0x900000 |
+|  197 | blk.21.attn_v.weight      |       0xb21c7980 |         0x240000 |
+|  198 | blk.21.ffn_down.weight    |       0xb2407980 |        0x2680000 |
+|  199 | blk.21.ffn_gate.weight    |       0xb4a87980 |        0x1f80000 |
+|  200 | blk.21.ffn_norm.weight    |       0xb6a07980 |           0x4000 |
+|  201 | blk.21.ffn_up.weight      |       0xb6a0b980 |        0x1f80000 |
+|  202 | blk.22.attn_k.weight      |       0xb898b980 |         0x240000 |
+|  203 | blk.22.attn_norm.weight   |       0xb8bcb980 |           0x4000 |
+|  204 | blk.22.attn_output.weight |       0xb8bcf980 |         0x900000 |
+|  205 | blk.22.attn_q.weight      |       0xb94cf980 |         0x900000 |
+|  206 | blk.22.attn_v.weight      |       0xb9dcf980 |         0x240000 |
+|  207 | blk.22.ffn_down.weight    |       0xba00f980 |        0x2680000 |
+|  208 | blk.22.ffn_gate.weight    |       0xbc68f980 |        0x1f80000 |
+|  209 | blk.22.ffn_norm.weight    |       0xbe60f980 |           0x4000 |
+|  210 | blk.22.ffn_up.weight      |       0xbe613980 |        0x1f80000 |
+|  211 | blk.23.attn_k.weight      |       0xc0593980 |         0x240000 |
+|  212 | blk.23.attn_norm.weight   |       0xc07d3980 |           0x4000 |
+|  213 | blk.23.attn_output.weight |       0xc07d7980 |         0x900000 |
+|  214 | blk.23.attn_q.weight      |       0xc10d7980 |         0x900000 |
+|  215 | blk.23.attn_v.weight      |       0xc19d7980 |         0x240000 |
+|  216 | blk.23.ffn_down.weight    |       0xc1c17980 |        0x2680000 |
+|  217 | blk.23.ffn_gate.weight    |       0xc4297980 |        0x1f80000 |
+|  218 | blk.23.ffn_norm.weight    |       0xc6217980 |           0x4000 |
+|  219 | blk.23.ffn_up.weight      |       0xc621b980 |        0x1f80000 |
+|  220 | blk.24.attn_k.weight      |       0xc819b980 |         0x240000 |
+|  221 | blk.24.attn_norm.weight   |       0xc83db980 |           0x4000 |
+|  222 | blk.24.attn_output.weight |       0xc83df980 |         0x900000 |
+|  223 | blk.24.attn_q.weight      |       0xc8cdf980 |         0x900000 |
+|  224 | blk.24.attn_v.weight      |       0xc95df980 |         0x240000 |
+|  225 | blk.24.ffn_down.weight    |       0xc981f980 |        0x2680000 |
+|  226 | blk.24.ffn_gate.weight    |       0xcbe9f980 |        0x1f80000 |
+|  227 | blk.24.ffn_norm.weight    |       0xcde1f980 |           0x4000 |
+|  228 | blk.24.ffn_up.weight      |       0xcde23980 |        0x1f80000 |
+|  229 | blk.25.attn_k.weight      |       0xcfda3980 |         0x240000 |
+|  230 | blk.25.attn_norm.weight   |       0xcffe3980 |           0x4000 |
+|  231 | blk.25.attn_output.weight |       0xcffe7980 |         0x900000 |
+|  232 | blk.25.attn_q.weight      |       0xd08e7980 |         0x900000 |
+|  233 | blk.25.attn_v.weight      |       0xd11e7980 |         0x240000 |
+|  234 | blk.25.ffn_down.weight    |       0xd1427980 |        0x2680000 |
+|  235 | blk.25.ffn_gate.weight    |       0xd3aa7980 |        0x1f80000 |
+|  236 | blk.25.ffn_norm.weight    |       0xd5a27980 |           0x4000 |
+|  237 | blk.25.ffn_up.weight      |       0xd5a2b980 |        0x1f80000 |
+|  238 | blk.26.attn_k.weight      |       0xd79ab980 |         0x240000 |
+|  239 | blk.26.attn_norm.weight   |       0xd7beb980 |           0x4000 |
+|  240 | blk.26.attn_output.weight |       0xd7bef980 |         0x900000 |
+|  241 | blk.26.attn_q.weight      |       0xd84ef980 |         0x900000 |
+|  242 | blk.26.attn_v.weight      |       0xd8def980 |         0x240000 |
+|  243 | blk.26.ffn_down.weight    |       0xd902f980 |        0x2680000 |
+|  244 | blk.26.ffn_gate.weight    |       0xdb6af980 |        0x1f80000 |
+|  245 | blk.26.ffn_norm.weight    |       0xdd62f980 |           0x4000 |
+|  246 | blk.26.ffn_up.weight      |       0xdd633980 |        0x1f80000 |
+|  247 | blk.27.attn_k.weight      |       0xdf5b3980 |         0x240000 |
+|  248 | blk.27.attn_norm.weight   |       0xdf7f3980 |           0x4000 |
+|  249 | blk.27.attn_output.weight |       0xdf7f7980 |         0x900000 |
+|  250 | blk.27.attn_q.weight      |       0xe00f7980 |         0x900000 |
+|  251 | blk.27.attn_v.weight      |       0xe09f7980 |         0x240000 |
+|  252 | blk.27.ffn_down.weight    |       0xe0c37980 |        0x2680000 |
+|  253 | blk.27.ffn_gate.weight    |       0xe32b7980 |        0x1f80000 |
+|  254 | blk.27.ffn_norm.weight    |       0xe5237980 |           0x4000 |
+|  255 | blk.27.ffn_up.weight      |       0xe523b980 |        0x1f80000 |
+|  256 | blk.28.attn_k.weight      |       0xe71bb980 |         0x240000 |
+|  257 | blk.28.attn_norm.weight   |       0xe73fb980 |           0x4000 |
+|  258 | blk.28.attn_output.weight |       0xe73ff980 |         0x900000 |
+|  259 | blk.28.attn_q.weight      |       0xe7cff980 |         0x900000 |
+|  260 | blk.28.attn_v.weight      |       0xe85ff980 |         0x240000 |
+|  261 | blk.28.ffn_down.weight    |       0xe883f980 |        0x2680000 |
+|  262 | blk.28.ffn_gate.weight    |       0xeaebf980 |        0x1f80000 |
+|  263 | blk.28.ffn_norm.weight    |       0xece3f980 |           0x4000 |
+|  264 | blk.28.ffn_up.weight      |       0xece43980 |        0x1f80000 |
+|  265 | blk.29.attn_k.weight      |       0xeedc3980 |         0x240000 |
+|  266 | blk.29.attn_norm.weight   |       0xef003980 |           0x4000 |
+|  267 | blk.29.attn_output.weight |       0xef007980 |         0x900000 |
+|  268 | blk.29.attn_q.weight      |       0xef907980 |         0x900000 |
+|  269 | blk.29.attn_v.weight      |       0xf0207980 |         0x240000 |
+|  270 | blk.29.ffn_down.weight    |       0xf0447980 |        0x2680000 |
+|  271 | blk.29.ffn_gate.weight    |       0xf2ac7980 |        0x1f80000 |
+|  272 | blk.29.ffn_norm.weight    |       0xf4a47980 |           0x4000 |
+|  273 | blk.29.ffn_up.weight      |       0xf4a4b980 |        0x1f80000 |
+|  274 | blk.30.attn_k.weight      |       0xf69cb980 |         0x240000 |
+|  275 | blk.30.attn_norm.weight   |       0xf6c0b980 |           0x4000 |
+|  276 | blk.30.attn_output.weight |       0xf6c0f980 |         0x900000 |
+|  277 | blk.30.attn_q.weight      |       0xf750f980 |         0x900000 |
+|  278 | blk.30.attn_v.weight      |       0xf7e0f980 |         0x240000 |
+|  279 | blk.30.ffn_down.weight    |       0xf804f980 |        0x2680000 |
+|  280 | blk.30.ffn_gate.weight    |       0xfa6cf980 |        0x1f80000 |
+|  281 | blk.30.ffn_norm.weight    |       0xfc64f980 |           0x4000 |
+|  282 | blk.30.ffn_up.weight      |       0xfc653980 |        0x1f80000 |
+|  283 | blk.31.attn_k.weight      |       0xfe5d3980 |         0x1b8000 |
+|  284 | blk.31.attn_norm.weight   |       0xfe78b980 |           0x4000 |
+|  285 | blk.31.attn_output.weight |       0xfe78f980 |         0x900000 |
+|  286 | blk.31.attn_q.weight      |       0xff08f980 |         0x6e0000 |
+|  287 | blk.31.attn_v.weight      |       0xff76f980 |         0x220000 |
+|  288 | blk.31.ffn_down.weight    |       0xff98f980 |        0x2680000 |
+|  289 | blk.31.ffn_gate.weight    |      0x10200f980 |        0x1f80000 |
+|  290 | blk.31.ffn_norm.weight    |      0x103f8f980 |           0x4000 |
+|  291 | blk.31.ffn_up.weight      |      0x103f93980 |        0x1f80000 |
+### <a name="base">Base Tensor Group : ~1B Elements</a>
+| T_ID | Tensor Layer Name  | Human Friendly Tensor Layer Name | Elements          | Shape                 | Type   |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-------|
+|    0 | output.weight      | Output (W)                       | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | IQ4_NL |
+|    1 | output_norm.weight | Output Normalization (W)         | (  ~4K)      4096 | 4096 x      1 x 1 x 1 | F32    |
+|    2 | rope_freqs.weight  | Rope_Freqs (W)                   | (   64)        64 |   64 x      1 x 1 x 1 | F32    |
+|    3 | token_embd.weight  | Token Embedding (W)              | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | IQ3_S  |
+- Total elements in base: ( ~1B) 1050677312
+- Percentage of total elements: 13.08%
+### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type   |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-------|
+|    4 | blk.0.attn_k.weight      | Block 0 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|    5 | blk.0.attn_norm.weight   | Block 0 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|    6 | blk.0.attn_output.weight | Block 0 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|    7 | blk.0.attn_q.weight      | Block 0 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|    8 | blk.0.attn_v.weight      | Block 0 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|    9 | blk.0.ffn_down.weight    | Block 0 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|   10 | blk.0.ffn_gate.weight    | Block 0 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|   11 | blk.0.ffn_norm.weight    | Block 0 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   12 | blk.0.ffn_up.weight      | Block 0 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.0: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type   |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-------|
+|   13 | blk.1.attn_k.weight      | Block 1 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|   14 | blk.1.attn_norm.weight   | Block 1 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   15 | blk.1.attn_output.weight | Block 1 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|   16 | blk.1.attn_q.weight      | Block 1 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|   17 | blk.1.attn_v.weight      | Block 1 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|   18 | blk.1.ffn_down.weight    | Block 1 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|   19 | blk.1.ffn_gate.weight    | Block 1 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|   20 | blk.1.ffn_norm.weight    | Block 1 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   21 | blk.1.ffn_up.weight      | Block 1 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.1: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type   |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-------|
+|   22 | blk.2.attn_k.weight      | Block 2 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|   23 | blk.2.attn_norm.weight   | Block 2 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   24 | blk.2.attn_output.weight | Block 2 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|   25 | blk.2.attn_q.weight      | Block 2 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|   26 | blk.2.attn_v.weight      | Block 2 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|   27 | blk.2.ffn_down.weight    | Block 2 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|   28 | blk.2.ffn_gate.weight    | Block 2 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|   29 | blk.2.ffn_norm.weight    | Block 2 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   30 | blk.2.ffn_up.weight      | Block 2 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.2: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type   |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-------|
+|   31 | blk.3.attn_k.weight      | Block 3 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|   32 | blk.3.attn_norm.weight   | Block 3 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   33 | blk.3.attn_output.weight | Block 3 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|   34 | blk.3.attn_q.weight      | Block 3 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|   35 | blk.3.attn_v.weight      | Block 3 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|   36 | blk.3.ffn_down.weight    | Block 3 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|   37 | blk.3.ffn_gate.weight    | Block 3 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|   38 | blk.3.ffn_norm.weight    | Block 3 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   39 | blk.3.ffn_up.weight      | Block 3 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.3: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type   |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-------|
+|   40 | blk.4.attn_k.weight      | Block 4 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|   41 | blk.4.attn_norm.weight   | Block 4 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   42 | blk.4.attn_output.weight | Block 4 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|   43 | blk.4.attn_q.weight      | Block 4 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|   44 | blk.4.attn_v.weight      | Block 4 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|   45 | blk.4.ffn_down.weight    | Block 4 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|   46 | blk.4.ffn_gate.weight    | Block 4 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|   47 | blk.4.ffn_norm.weight    | Block 4 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   48 | blk.4.ffn_up.weight      | Block 4 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.4: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type   |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-------|
+|   49 | blk.5.attn_k.weight      | Block 5 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|   50 | blk.5.attn_norm.weight   | Block 5 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   51 | blk.5.attn_output.weight | Block 5 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|   52 | blk.5.attn_q.weight      | Block 5 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|   53 | blk.5.attn_v.weight      | Block 5 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|   54 | blk.5.ffn_down.weight    | Block 5 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|   55 | blk.5.ffn_gate.weight    | Block 5 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|   56 | blk.5.ffn_norm.weight    | Block 5 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   57 | blk.5.ffn_up.weight      | Block 5 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.5: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type   |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-------|
+|   58 | blk.6.attn_k.weight      | Block 6 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|   59 | blk.6.attn_norm.weight   | Block 6 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   60 | blk.6.attn_output.weight | Block 6 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|   61 | blk.6.attn_q.weight      | Block 6 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|   62 | blk.6.attn_v.weight      | Block 6 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|   63 | blk.6.ffn_down.weight    | Block 6 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|   64 | blk.6.ffn_gate.weight    | Block 6 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|   65 | blk.6.ffn_norm.weight    | Block 6 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   66 | blk.6.ffn_up.weight      | Block 6 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.6: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type   |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-------|
+|   67 | blk.7.attn_k.weight      | Block 7 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|   68 | blk.7.attn_norm.weight   | Block 7 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   69 | blk.7.attn_output.weight | Block 7 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|   70 | blk.7.attn_q.weight      | Block 7 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|   71 | blk.7.attn_v.weight      | Block 7 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|   72 | blk.7.ffn_down.weight    | Block 7 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|   73 | blk.7.ffn_gate.weight    | Block 7 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|   74 | blk.7.ffn_norm.weight    | Block 7 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   75 | blk.7.ffn_up.weight      | Block 7 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.7: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type   |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-------|
+|   76 | blk.8.attn_k.weight      | Block 8 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|   77 | blk.8.attn_norm.weight   | Block 8 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   78 | blk.8.attn_output.weight | Block 8 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|   79 | blk.8.attn_q.weight      | Block 8 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|   80 | blk.8.attn_v.weight      | Block 8 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|   81 | blk.8.ffn_down.weight    | Block 8 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|   82 | blk.8.ffn_gate.weight    | Block 8 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|   83 | blk.8.ffn_norm.weight    | Block 8 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   84 | blk.8.ffn_up.weight      | Block 8 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.8: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type   |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-------|
+|   85 | blk.9.attn_k.weight      | Block 9 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|   86 | blk.9.attn_norm.weight   | Block 9 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   87 | blk.9.attn_output.weight | Block 9 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|   88 | blk.9.attn_q.weight      | Block 9 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|   89 | blk.9.attn_v.weight      | Block 9 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|   90 | blk.9.ffn_down.weight    | Block 9 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|   91 | blk.9.ffn_gate.weight    | Block 9 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|   92 | blk.9.ffn_norm.weight    | Block 9 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   93 | blk.9.ffn_up.weight      | Block 9 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.9: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|   94 | blk.10.attn_k.weight      | Block 10 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|   95 | blk.10.attn_norm.weight   | Block 10 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|   96 | blk.10.attn_output.weight | Block 10 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|   97 | blk.10.attn_q.weight      | Block 10 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|   98 | blk.10.attn_v.weight      | Block 10 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|   99 | blk.10.ffn_down.weight    | Block 10 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  100 | blk.10.ffn_gate.weight    | Block 10 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  101 | blk.10.ffn_norm.weight    | Block 10 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  102 | blk.10.ffn_up.weight      | Block 10 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.10: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  103 | blk.11.attn_k.weight      | Block 11 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  104 | blk.11.attn_norm.weight   | Block 11 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  105 | blk.11.attn_output.weight | Block 11 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  106 | blk.11.attn_q.weight      | Block 11 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  107 | blk.11.attn_v.weight      | Block 11 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|  108 | blk.11.ffn_down.weight    | Block 11 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  109 | blk.11.ffn_gate.weight    | Block 11 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  110 | blk.11.ffn_norm.weight    | Block 11 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  111 | blk.11.ffn_up.weight      | Block 11 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.11: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  112 | blk.12.attn_k.weight      | Block 12 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  113 | blk.12.attn_norm.weight   | Block 12 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  114 | blk.12.attn_output.weight | Block 12 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  115 | blk.12.attn_q.weight      | Block 12 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  116 | blk.12.attn_v.weight      | Block 12 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|  117 | blk.12.ffn_down.weight    | Block 12 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  118 | blk.12.ffn_gate.weight    | Block 12 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  119 | blk.12.ffn_norm.weight    | Block 12 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  120 | blk.12.ffn_up.weight      | Block 12 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.12: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  121 | blk.13.attn_k.weight      | Block 13 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  122 | blk.13.attn_norm.weight   | Block 13 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  123 | blk.13.attn_output.weight | Block 13 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  124 | blk.13.attn_q.weight      | Block 13 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  125 | blk.13.attn_v.weight      | Block 13 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  126 | blk.13.ffn_down.weight    | Block 13 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  127 | blk.13.ffn_gate.weight    | Block 13 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  128 | blk.13.ffn_norm.weight    | Block 13 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  129 | blk.13.ffn_up.weight      | Block 13 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.13: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  130 | blk.14.attn_k.weight      | Block 14 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  131 | blk.14.attn_norm.weight   | Block 14 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  132 | blk.14.attn_output.weight | Block 14 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  133 | blk.14.attn_q.weight      | Block 14 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  134 | blk.14.attn_v.weight      | Block 14 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  135 | blk.14.ffn_down.weight    | Block 14 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  136 | blk.14.ffn_gate.weight    | Block 14 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  137 | blk.14.ffn_norm.weight    | Block 14 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  138 | blk.14.ffn_up.weight      | Block 14 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.14: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  139 | blk.15.attn_k.weight      | Block 15 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  140 | blk.15.attn_norm.weight   | Block 15 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  141 | blk.15.attn_output.weight | Block 15 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  142 | blk.15.attn_q.weight      | Block 15 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  143 | blk.15.attn_v.weight      | Block 15 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|  144 | blk.15.ffn_down.weight    | Block 15 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  145 | blk.15.ffn_gate.weight    | Block 15 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+|  146 | blk.15.ffn_norm.weight    | Block 15 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  147 | blk.15.ffn_up.weight      | Block 15 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ3_S  |
+- Total elements in blk.15: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  148 | blk.16.attn_k.weight      | Block 16 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  149 | blk.16.attn_norm.weight   | Block 16 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  150 | blk.16.attn_output.weight | Block 16 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  151 | blk.16.attn_q.weight      | Block 16 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  152 | blk.16.attn_v.weight      | Block 16 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  153 | blk.16.ffn_down.weight    | Block 16 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  154 | blk.16.ffn_gate.weight    | Block 16 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  155 | blk.16.ffn_norm.weight    | Block 16 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  156 | blk.16.ffn_up.weight      | Block 16 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.16: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  157 | blk.17.attn_k.weight      | Block 17 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  158 | blk.17.attn_norm.weight   | Block 17 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  159 | blk.17.attn_output.weight | Block 17 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  160 | blk.17.attn_q.weight      | Block 17 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  161 | blk.17.attn_v.weight      | Block 17 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|  162 | blk.17.ffn_down.weight    | Block 17 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  163 | blk.17.ffn_gate.weight    | Block 17 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  164 | blk.17.ffn_norm.weight    | Block 17 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  165 | blk.17.ffn_up.weight      | Block 17 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.17: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  166 | blk.18.attn_k.weight      | Block 18 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  167 | blk.18.attn_norm.weight   | Block 18 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  168 | blk.18.attn_output.weight | Block 18 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  169 | blk.18.attn_q.weight      | Block 18 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  170 | blk.18.attn_v.weight      | Block 18 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  171 | blk.18.ffn_down.weight    | Block 18 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  172 | blk.18.ffn_gate.weight    | Block 18 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  173 | blk.18.ffn_norm.weight    | Block 18 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  174 | blk.18.ffn_up.weight      | Block 18 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.18: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  175 | blk.19.attn_k.weight      | Block 19 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  176 | blk.19.attn_norm.weight   | Block 19 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  177 | blk.19.attn_output.weight | Block 19 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  178 | blk.19.attn_q.weight      | Block 19 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  179 | blk.19.attn_v.weight      | Block 19 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  180 | blk.19.ffn_down.weight    | Block 19 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  181 | blk.19.ffn_gate.weight    | Block 19 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  182 | blk.19.ffn_norm.weight    | Block 19 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  183 | blk.19.ffn_up.weight      | Block 19 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.19: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  184 | blk.20.attn_k.weight      | Block 20 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  185 | blk.20.attn_norm.weight   | Block 20 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  186 | blk.20.attn_output.weight | Block 20 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  187 | blk.20.attn_q.weight      | Block 20 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  188 | blk.20.attn_v.weight      | Block 20 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  189 | blk.20.ffn_down.weight    | Block 20 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  190 | blk.20.ffn_gate.weight    | Block 20 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  191 | blk.20.ffn_norm.weight    | Block 20 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  192 | blk.20.ffn_up.weight      | Block 20 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.20: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  193 | blk.21.attn_k.weight      | Block 21 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  194 | blk.21.attn_norm.weight   | Block 21 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  195 | blk.21.attn_output.weight | Block 21 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  196 | blk.21.attn_q.weight      | Block 21 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  197 | blk.21.attn_v.weight      | Block 21 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  198 | blk.21.ffn_down.weight    | Block 21 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  199 | blk.21.ffn_gate.weight    | Block 21 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  200 | blk.21.ffn_norm.weight    | Block 21 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  201 | blk.21.ffn_up.weight      | Block 21 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.21: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  202 | blk.22.attn_k.weight      | Block 22 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  203 | blk.22.attn_norm.weight   | Block 22 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  204 | blk.22.attn_output.weight | Block 22 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  205 | blk.22.attn_q.weight      | Block 22 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  206 | blk.22.attn_v.weight      | Block 22 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  207 | blk.22.ffn_down.weight    | Block 22 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  208 | blk.22.ffn_gate.weight    | Block 22 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  209 | blk.22.ffn_norm.weight    | Block 22 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  210 | blk.22.ffn_up.weight      | Block 22 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.22: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  211 | blk.23.attn_k.weight      | Block 23 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  212 | blk.23.attn_norm.weight   | Block 23 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  213 | blk.23.attn_output.weight | Block 23 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  214 | blk.23.attn_q.weight      | Block 23 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  215 | blk.23.attn_v.weight      | Block 23 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  216 | blk.23.ffn_down.weight    | Block 23 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  217 | blk.23.ffn_gate.weight    | Block 23 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  218 | blk.23.ffn_norm.weight    | Block 23 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  219 | blk.23.ffn_up.weight      | Block 23 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.23: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  220 | blk.24.attn_k.weight      | Block 24 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  221 | blk.24.attn_norm.weight   | Block 24 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  222 | blk.24.attn_output.weight | Block 24 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  223 | blk.24.attn_q.weight      | Block 24 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  224 | blk.24.attn_v.weight      | Block 24 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  225 | blk.24.ffn_down.weight    | Block 24 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  226 | blk.24.ffn_gate.weight    | Block 24 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  227 | blk.24.ffn_norm.weight    | Block 24 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  228 | blk.24.ffn_up.weight      | Block 24 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.24: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  229 | blk.25.attn_k.weight      | Block 25 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  230 | blk.25.attn_norm.weight   | Block 25 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  231 | blk.25.attn_output.weight | Block 25 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  232 | blk.25.attn_q.weight      | Block 25 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  233 | blk.25.attn_v.weight      | Block 25 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  234 | blk.25.ffn_down.weight    | Block 25 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  235 | blk.25.ffn_gate.weight    | Block 25 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  236 | blk.25.ffn_norm.weight    | Block 25 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  237 | blk.25.ffn_up.weight      | Block 25 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.25: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  238 | blk.26.attn_k.weight      | Block 26 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  239 | blk.26.attn_norm.weight   | Block 26 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  240 | blk.26.attn_output.weight | Block 26 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  241 | blk.26.attn_q.weight      | Block 26 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  242 | blk.26.attn_v.weight      | Block 26 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  243 | blk.26.ffn_down.weight    | Block 26 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  244 | blk.26.ffn_gate.weight    | Block 26 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  245 | blk.26.ffn_norm.weight    | Block 26 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  246 | blk.26.ffn_up.weight      | Block 26 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.26: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  247 | blk.27.attn_k.weight      | Block 27 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  248 | blk.27.attn_norm.weight   | Block 27 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  249 | blk.27.attn_output.weight | Block 27 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  250 | blk.27.attn_q.weight      | Block 27 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  251 | blk.27.attn_v.weight      | Block 27 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  252 | blk.27.ffn_down.weight    | Block 27 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  253 | blk.27.ffn_gate.weight    | Block 27 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  254 | blk.27.ffn_norm.weight    | Block 27 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  255 | blk.27.ffn_up.weight      | Block 27 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.27: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  256 | blk.28.attn_k.weight      | Block 28 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  257 | blk.28.attn_norm.weight   | Block 28 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  258 | blk.28.attn_output.weight | Block 28 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  259 | blk.28.attn_q.weight      | Block 28 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  260 | blk.28.attn_v.weight      | Block 28 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  261 | blk.28.ffn_down.weight    | Block 28 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  262 | blk.28.ffn_gate.weight    | Block 28 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  263 | blk.28.ffn_norm.weight    | Block 28 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  264 | blk.28.ffn_up.weight      | Block 28 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.28: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  265 | blk.29.attn_k.weight      | Block 29 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  266 | blk.29.attn_norm.weight   | Block 29 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  267 | blk.29.attn_output.weight | Block 29 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  268 | blk.29.attn_q.weight      | Block 29 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  269 | blk.29.attn_v.weight      | Block 29 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  270 | blk.29.ffn_down.weight    | Block 29 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  271 | blk.29.ffn_gate.weight    | Block 29 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  272 | blk.29.ffn_norm.weight    | Block 29 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  273 | blk.29.ffn_up.weight      | Block 29 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.29: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  274 | blk.30.attn_k.weight      | Block 30 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  275 | blk.30.attn_norm.weight   | Block 30 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  276 | blk.30.attn_output.weight | Block 30 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  277 | blk.30.attn_q.weight      | Block 30 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  278 | blk.30.attn_v.weight      | Block 30 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_NL |
+|  279 | blk.30.ffn_down.weight    | Block 30 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  280 | blk.30.ffn_gate.weight    | Block 30 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  281 | blk.30.ffn_norm.weight    | Block 30 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  282 | blk.30.ffn_up.weight      | Block 30 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.30: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type   |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-------|
+|  283 | blk.31.attn_k.weight      | Block 31 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ3_S  |
+|  284 | blk.31.attn_norm.weight   | Block 31 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  285 | blk.31.attn_output.weight | Block 31 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ4_NL |
+|  286 | blk.31.attn_q.weight      | Block 31 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | IQ3_S  |
+|  287 | blk.31.attn_v.weight      | Block 31 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | IQ4_XS |
+|  288 | blk.31.ffn_down.weight    | Block 31 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K   |
+|  289 | blk.31.ffn_gate.weight    | Block 31 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+|  290 | blk.31.ffn_norm.weight    | Block 31 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32    |
+|  291 | blk.31.ffn_up.weight      | Block 31 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | IQ4_NL |
+- Total elements in blk.31: (~218M) 218112000
+- Percentage of total elements: 2.72%

scores/Llama-Guard-3-8B-Q3_K_L.md ADDED Viewed

	@@ -0,0 +1,978 @@

+# Llama-Guard-3-8B-Q3_K_L.gguf - GGUF Internal File Dump
+- Endian: LITTLE endian
+## Key Value Metadata Store
+There are 39 key-value pairs in this file
+| POS | TYPE     |  Count | Key                                    | Value                                                               |
+|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
+|   1 | UINT32   |      1 | GGUF.version                           | 3                                                                   |
+|   2 | UINT64   |      1 | GGUF.tensor_count                      | 292                                                                 |
+|   3 | UINT64   |      1 | GGUF.kv_count                          | 36                                                                  |
+|   4 | STRING   |      1 | general.architecture                   | `llama`                                                             |
+|   5 | STRING   |      1 | general.type                           | `model`                                                             |
+|   6 | STRING   |      1 | general.name                           | `Llama Guard 3 8B`                                                  |
+|   7 | STRING   |      1 | general.basename                       | `Llama-Guard-3`                                                     |
+|   8 | STRING   |      1 | general.size_label                     | `8B`                                                                |
+|   9 | STRING   |      1 | general.license                        | `llama3.1`                                                          |
+|  10 | UINT32   |      1 | general.base_model.count               | 1                                                                   |
+|  11 | STRING   |      1 | general.base_model.0.name              | `Meta Llama 3.1 8B`                                                 |
+|  12 | STRING   |      1 | general.base_model.0.organization      | `Meta Llama`                                                        |
+|  13 | STRING   |      1 | general.base_model.0.repo_url          | `https://huggingface.co/meta-llama/Meta-Llama-3.1-8B`               |
+|  14 | [STRING] |      6 | general.tags                           | [ `facebook`, `meta`, `pytorch`, `llama`, `llama-3`, ... ]          |
+|  15 | [STRING] |      1 | general.languages                      | [ `en` ]                                                            |
+|  16 | UINT32   |      1 | llama.block_count                      | 32                                                                  |
+|  17 | UINT32   |      1 | llama.context_length                   | 131072                                                              |
+|  18 | UINT32   |      1 | llama.embedding_length                 | 4096                                                                |
+|  19 | UINT32   |      1 | llama.feed_forward_length              | 14336                                                               |
+|  20 | UINT32   |      1 | llama.attention.head_count             | 32                                                                  |
+|  21 | UINT32   |      1 | llama.attention.head_count_kv          | 8                                                                   |
+|  22 | FLOAT32  |      1 | llama.rope.freq_base                   | 500000.0                                                            |
+|  23 | FLOAT32  |      1 | llama.attention.layer_norm_rms_epsilon | 1e-05                                                               |
+|  24 | UINT32   |      1 | llama.vocab_size                       | 128256                                                              |
+|  25 | UINT32   |      1 | llama.rope.dimension_count             | 128                                                                 |
+|  26 | STRING   |      1 | tokenizer.ggml.model                   | `gpt2`                                                              |
+|  27 | STRING   |      1 | tokenizer.ggml.pre                     | `smaug-bpe`                                                         |
+|  28 | [STRING] | 128256 | tokenizer.ggml.tokens                  | [ `!`, `"`, `#`, `$`, `%`, ... ]                                    |
+|  29 | [INT32]  | 128256 | tokenizer.ggml.token_type              | [ 1, 1, 1, 1, 1, 1, 1, ... ]                                        |
+|  30 | [STRING] | 280147 | tokenizer.ggml.merges                  | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]                    |
+|  31 | UINT32   |      1 | tokenizer.ggml.bos_token_id            | 128000                                                              |
+|  32 | UINT32   |      1 | tokenizer.ggml.eos_token_id            | 128009                                                              |
+|  33 | STRING   |      1 | tokenizer.chat_template                | `{% if messages|length % 2 == 0`...`assistant<|end_header_id|>" }}` |
+|  34 | UINT32   |      1 | general.quantization_version           | 2                                                                   |
+|  35 | UINT32   |      1 | general.file_type                      | 13                                                                  |
+|  36 | STRING   |      1 | quantize.imatrix.file                  | `./imatrix/imatrix-Llama-Guard-3-8B-small.dat`                      |
+|  37 | STRING   |      1 | quantize.imatrix.dataset               | `../../datasets/imatrix/calibration_eur_small.txt`                  |
+|  38 | INT32    |      1 | quantize.imatrix.entries_count         | 224                                                                 |
+|  39 | INT32    |      1 | quantize.imatrix.chunks_count          | 962                                                                 |
+## Tensors Overview ~8B Elements
+Total number of elements in all tensors: 8030261312 Elements
+- [Llama-Guard-3-8B-Q3\_K\_L.gguf - GGUF Internal File Dump](#llama-guard-3-8b-q3_k_lgguf---gguf-internal-file-dump)
+  - [Key Value Metadata Store](#key-value-metadata-store)
+  - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
+    - [Tensor Data Offset](#tensor-data-offset)
+    - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
+    - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
+    - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
+    - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
+    - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
+    - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
+    - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
+    - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
+    - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
+    - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
+    - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
+    - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
+    - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
+    - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
+    - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
+    - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
+    - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
+    - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
+    - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
+    - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
+    - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
+    - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
+    - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
+    - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
+    - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
+    - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
+    - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
+    - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
+    - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
+    - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
+    - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
+    - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
+    - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
+### Tensor Data Offset
+This table contains the offset and data segment relative to start of file
+| T_ID | Tensor Layer Name         |  Data Offset (B) |    Data Size (B) |
+|-----:|:--------------------------|-----------------:|-----------------:|
+|    0 | output.weight             |         0x779880 |        0xd746000 |
+|    1 | output_norm.weight        |        0xdebf880 |           0x4000 |
+|    2 | rope_freqs.weight         |        0xdec3880 |            0x100 |
+|    3 | token_embd.weight         |        0xdec3980 |        0xd746000 |
+|    4 | blk.0.attn_k.weight       |       0x1b609980 |         0x150000 |
+|    5 | blk.0.attn_norm.weight    |       0x1b759980 |           0x4000 |
+|    6 | blk.0.attn_output.weight  |       0x1b75d980 |         0xb00000 |
+|    7 | blk.0.attn_q.weight       |       0x1c25d980 |         0x540000 |
+|    8 | blk.0.attn_v.weight       |       0x1c79d980 |         0x240000 |
+|    9 | blk.0.ffn_down.weight     |       0x1c9dd980 |        0x1f80000 |
+|   10 | blk.0.ffn_gate.weight     |       0x1e95d980 |        0x1260000 |
+|   11 | blk.0.ffn_norm.weight     |       0x1fbbd980 |           0x4000 |
+|   12 | blk.0.ffn_up.weight       |       0x1fbc1980 |        0x1260000 |
+|   13 | blk.1.attn_k.weight       |       0x20e21980 |         0x150000 |
+|   14 | blk.1.attn_norm.weight    |       0x20f71980 |           0x4000 |
+|   15 | blk.1.attn_output.weight  |       0x20f75980 |         0xb00000 |
+|   16 | blk.1.attn_q.weight       |       0x21a75980 |         0x540000 |
+|   17 | blk.1.attn_v.weight       |       0x21fb5980 |         0x240000 |
+|   18 | blk.1.ffn_down.weight     |       0x221f5980 |        0x2680000 |
+|   19 | blk.1.ffn_gate.weight     |       0x24875980 |        0x1260000 |
+|   20 | blk.1.ffn_norm.weight     |       0x25ad5980 |           0x4000 |
+|   21 | blk.1.ffn_up.weight       |       0x25ad9980 |        0x1260000 |
+|   22 | blk.2.attn_k.weight       |       0x26d39980 |         0x150000 |
+|   23 | blk.2.attn_norm.weight    |       0x26e89980 |           0x4000 |
+|   24 | blk.2.attn_output.weight  |       0x26e8d980 |         0xb00000 |
+|   25 | blk.2.attn_q.weight       |       0x2798d980 |         0x540000 |
+|   26 | blk.2.attn_v.weight       |       0x27ecd980 |         0x240000 |
+|   27 | blk.2.ffn_down.weight     |       0x2810d980 |        0x1f80000 |
+|   28 | blk.2.ffn_gate.weight     |       0x2a08d980 |        0x1260000 |
+|   29 | blk.2.ffn_norm.weight     |       0x2b2ed980 |           0x4000 |
+|   30 | blk.2.ffn_up.weight       |       0x2b2f1980 |        0x1260000 |
+|   31 | blk.3.attn_k.weight       |       0x2c551980 |         0x150000 |
+|   32 | blk.3.attn_norm.weight    |       0x2c6a1980 |           0x4000 |
+|   33 | blk.3.attn_output.weight  |       0x2c6a5980 |         0xb00000 |
+|   34 | blk.3.attn_q.weight       |       0x2d1a5980 |         0x540000 |
+|   35 | blk.3.attn_v.weight       |       0x2d6e5980 |         0x240000 |
+|   36 | blk.3.ffn_down.weight     |       0x2d925980 |        0x1f80000 |
+|   37 | blk.3.ffn_gate.weight     |       0x2f8a5980 |        0x1260000 |
+|   38 | blk.3.ffn_norm.weight     |       0x30b05980 |           0x4000 |
+|   39 | blk.3.ffn_up.weight       |       0x30b09980 |        0x1260000 |
+|   40 | blk.4.attn_k.weight       |       0x31d69980 |         0x150000 |
+|   41 | blk.4.attn_norm.weight    |       0x31eb9980 |           0x4000 |
+|   42 | blk.4.attn_output.weight  |       0x31ebd980 |         0xb00000 |
+|   43 | blk.4.attn_q.weight       |       0x329bd980 |         0x540000 |
+|   44 | blk.4.attn_v.weight       |       0x32efd980 |         0x240000 |
+|   45 | blk.4.ffn_down.weight     |       0x3313d980 |        0x1f80000 |
+|   46 | blk.4.ffn_gate.weight     |       0x350bd980 |        0x1260000 |
+|   47 | blk.4.ffn_norm.weight     |       0x3631d980 |           0x4000 |
+|   48 | blk.4.ffn_up.weight       |       0x36321980 |        0x1260000 |
+|   49 | blk.5.attn_k.weight       |       0x37581980 |         0x150000 |
+|   50 | blk.5.attn_norm.weight    |       0x376d1980 |           0x4000 |
+|   51 | blk.5.attn_output.weight  |       0x376d5980 |         0xb00000 |
+|   52 | blk.5.attn_q.weight       |       0x381d5980 |         0x540000 |
+|   53 | blk.5.attn_v.weight       |       0x38715980 |         0x240000 |
+|   54 | blk.5.ffn_down.weight     |       0x38955980 |        0x1f80000 |
+|   55 | blk.5.ffn_gate.weight     |       0x3a8d5980 |        0x1260000 |
+|   56 | blk.5.ffn_norm.weight     |       0x3bb35980 |           0x4000 |
+|   57 | blk.5.ffn_up.weight       |       0x3bb39980 |        0x1260000 |
+|   58 | blk.6.attn_k.weight       |       0x3cd99980 |         0x150000 |
+|   59 | blk.6.attn_norm.weight    |       0x3cee9980 |           0x4000 |
+|   60 | blk.6.attn_output.weight  |       0x3ceed980 |         0xb00000 |
+|   61 | blk.6.attn_q.weight       |       0x3d9ed980 |         0x540000 |
+|   62 | blk.6.attn_v.weight       |       0x3df2d980 |         0x240000 |
+|   63 | blk.6.ffn_down.weight     |       0x3e16d980 |        0x1f80000 |
+|   64 | blk.6.ffn_gate.weight     |       0x400ed980 |        0x1260000 |
+|   65 | blk.6.ffn_norm.weight     |       0x4134d980 |           0x4000 |
+|   66 | blk.6.ffn_up.weight       |       0x41351980 |        0x1260000 |
+|   67 | blk.7.attn_k.weight       |       0x425b1980 |         0x150000 |
+|   68 | blk.7.attn_norm.weight    |       0x42701980 |           0x4000 |
+|   69 | blk.7.attn_output.weight  |       0x42705980 |         0xb00000 |
+|   70 | blk.7.attn_q.weight       |       0x43205980 |         0x540000 |
+|   71 | blk.7.attn_v.weight       |       0x43745980 |         0x240000 |
+|   72 | blk.7.ffn_down.weight     |       0x43985980 |        0x1f80000 |
+|   73 | blk.7.ffn_gate.weight     |       0x45905980 |        0x1260000 |
+|   74 | blk.7.ffn_norm.weight     |       0x46b65980 |           0x4000 |
+|   75 | blk.7.ffn_up.weight       |       0x46b69980 |        0x1260000 |
+|   76 | blk.8.attn_k.weight       |       0x47dc9980 |         0x150000 |
+|   77 | blk.8.attn_norm.weight    |       0x47f19980 |           0x4000 |
+|   78 | blk.8.attn_output.weight  |       0x47f1d980 |         0xb00000 |
+|   79 | blk.8.attn_q.weight       |       0x48a1d980 |         0x540000 |
+|   80 | blk.8.attn_v.weight       |       0x48f5d980 |         0x240000 |
+|   81 | blk.8.ffn_down.weight     |       0x4919d980 |        0x1f80000 |
+|   82 | blk.8.ffn_gate.weight     |       0x4b11d980 |        0x1260000 |
+|   83 | blk.8.ffn_norm.weight     |       0x4c37d980 |           0x4000 |
+|   84 | blk.8.ffn_up.weight       |       0x4c381980 |        0x1260000 |
+|   85 | blk.9.attn_k.weight       |       0x4d5e1980 |         0x150000 |
+|   86 | blk.9.attn_norm.weight    |       0x4d731980 |           0x4000 |
+|   87 | blk.9.attn_output.weight  |       0x4d735980 |         0xb00000 |
+|   88 | blk.9.attn_q.weight       |       0x4e235980 |         0x540000 |
+|   89 | blk.9.attn_v.weight       |       0x4e775980 |         0x240000 |
+|   90 | blk.9.ffn_down.weight     |       0x4e9b5980 |        0x1f80000 |
+|   91 | blk.9.ffn_gate.weight     |       0x50935980 |        0x1260000 |
+|   92 | blk.9.ffn_norm.weight     |       0x51b95980 |           0x4000 |
+|   93 | blk.9.ffn_up.weight       |       0x51b99980 |        0x1260000 |
+|   94 | blk.10.attn_k.weight      |       0x52df9980 |         0x150000 |
+|   95 | blk.10.attn_norm.weight   |       0x52f49980 |           0x4000 |
+|   96 | blk.10.attn_output.weight |       0x52f4d980 |         0xb00000 |
+|   97 | blk.10.attn_q.weight      |       0x53a4d980 |         0x540000 |
+|   98 | blk.10.attn_v.weight      |       0x53f8d980 |         0x240000 |
+|   99 | blk.10.ffn_down.weight    |       0x541cd980 |        0x1f80000 |
+|  100 | blk.10.ffn_gate.weight    |       0x5614d980 |        0x1260000 |
+|  101 | blk.10.ffn_norm.weight    |       0x573ad980 |           0x4000 |
+|  102 | blk.10.ffn_up.weight      |       0x573b1980 |        0x1260000 |
+|  103 | blk.11.attn_k.weight      |       0x58611980 |         0x150000 |
+|  104 | blk.11.attn_norm.weight   |       0x58761980 |           0x4000 |
+|  105 | blk.11.attn_output.weight |       0x58765980 |         0xb00000 |
+|  106 | blk.11.attn_q.weight      |       0x59265980 |         0x540000 |
+|  107 | blk.11.attn_v.weight      |       0x597a5980 |         0x240000 |
+|  108 | blk.11.ffn_down.weight    |       0x599e5980 |        0x1f80000 |
+|  109 | blk.11.ffn_gate.weight    |       0x5b965980 |        0x1260000 |
+|  110 | blk.11.ffn_norm.weight    |       0x5cbc5980 |           0x4000 |
+|  111 | blk.11.ffn_up.weight      |       0x5cbc9980 |        0x1260000 |
+|  112 | blk.12.attn_k.weight      |       0x5de29980 |         0x150000 |
+|  113 | blk.12.attn_norm.weight   |       0x5df79980 |           0x4000 |
+|  114 | blk.12.attn_output.weight |       0x5df7d980 |         0xb00000 |
+|  115 | blk.12.attn_q.weight      |       0x5ea7d980 |         0x540000 |
+|  116 | blk.12.attn_v.weight      |       0x5efbd980 |         0x240000 |
+|  117 | blk.12.ffn_down.weight    |       0x5f1fd980 |        0x1f80000 |
+|  118 | blk.12.ffn_gate.weight    |       0x6117d980 |        0x1260000 |
+|  119 | blk.12.ffn_norm.weight    |       0x623dd980 |           0x4000 |
+|  120 | blk.12.ffn_up.weight      |       0x623e1980 |        0x1260000 |
+|  121 | blk.13.attn_k.weight      |       0x63641980 |         0x1b8000 |
+|  122 | blk.13.attn_norm.weight   |       0x637f9980 |           0x4000 |
+|  123 | blk.13.attn_output.weight |       0x637fd980 |         0xb00000 |
+|  124 | blk.13.attn_q.weight      |       0x642fd980 |         0x6e0000 |
+|  125 | blk.13.attn_v.weight      |       0x649dd980 |         0x240000 |
+|  126 | blk.13.ffn_down.weight    |       0x64c1d980 |        0x1f80000 |
+|  127 | blk.13.ffn_gate.weight    |       0x66b9d980 |        0x1260000 |
+|  128 | blk.13.ffn_norm.weight    |       0x67dfd980 |           0x4000 |
+|  129 | blk.13.ffn_up.weight      |       0x67e01980 |        0x1260000 |
+|  130 | blk.14.attn_k.weight      |       0x69061980 |         0x1b8000 |
+|  131 | blk.14.attn_norm.weight   |       0x69219980 |           0x4000 |
+|  132 | blk.14.attn_output.weight |       0x6921d980 |         0xb00000 |
+|  133 | blk.14.attn_q.weight      |       0x69d1d980 |         0x6e0000 |
+|  134 | blk.14.attn_v.weight      |       0x6a3fd980 |         0x240000 |
+|  135 | blk.14.ffn_down.weight    |       0x6a63d980 |        0x1f80000 |
+|  136 | blk.14.ffn_gate.weight    |       0x6c5bd980 |        0x1260000 |
+|  137 | blk.14.ffn_norm.weight    |       0x6d81d980 |           0x4000 |
+|  138 | blk.14.ffn_up.weight      |       0x6d821980 |        0x1260000 |
+|  139 | blk.15.attn_k.weight      |       0x6ea81980 |         0x150000 |
+|  140 | blk.15.attn_norm.weight   |       0x6ebd1980 |           0x4000 |
+|  141 | blk.15.attn_output.weight |       0x6ebd5980 |         0xb00000 |
+|  142 | blk.15.attn_q.weight      |       0x6f6d5980 |         0x540000 |
+|  143 | blk.15.attn_v.weight      |       0x6fc15980 |         0x240000 |
+|  144 | blk.15.ffn_down.weight    |       0x6fe55980 |        0x1f80000 |
+|  145 | blk.15.ffn_gate.weight    |       0x71dd5980 |        0x1260000 |
+|  146 | blk.15.ffn_norm.weight    |       0x73035980 |           0x4000 |
+|  147 | blk.15.ffn_up.weight      |       0x73039980 |        0x1260000 |
+|  148 | blk.16.attn_k.weight      |       0x74299980 |         0x1b8000 |
+|  149 | blk.16.attn_norm.weight   |       0x74451980 |           0x4000 |
+|  150 | blk.16.attn_output.weight |       0x74455980 |         0xb00000 |
+|  151 | blk.16.attn_q.weight      |       0x74f55980 |         0x6e0000 |
+|  152 | blk.16.attn_v.weight      |       0x75635980 |         0x240000 |
+|  153 | blk.16.ffn_down.weight    |       0x75875980 |        0x1f80000 |
+|  154 | blk.16.ffn_gate.weight    |       0x777f5980 |        0x1810000 |
+|  155 | blk.16.ffn_norm.weight    |       0x79005980 |           0x4000 |
+|  156 | blk.16.ffn_up.weight      |       0x79009980 |        0x1810000 |
+|  157 | blk.17.attn_k.weight      |       0x7a819980 |         0x150000 |
+|  158 | blk.17.attn_norm.weight   |       0x7a969980 |           0x4000 |
+|  159 | blk.17.attn_output.weight |       0x7a96d980 |         0xb00000 |
+|  160 | blk.17.attn_q.weight      |       0x7b46d980 |         0x540000 |
+|  161 | blk.17.attn_v.weight      |       0x7b9ad980 |         0x240000 |
+|  162 | blk.17.ffn_down.weight    |       0x7bbed980 |        0x2680000 |
+|  163 | blk.17.ffn_gate.weight    |       0x7e26d980 |        0x1810000 |
+|  164 | blk.17.ffn_norm.weight    |       0x7fa7d980 |           0x4000 |
+|  165 | blk.17.ffn_up.weight      |       0x7fa81980 |        0x1810000 |
+|  166 | blk.18.attn_k.weight      |       0x81291980 |         0x1b8000 |
+|  167 | blk.18.attn_norm.weight   |       0x81449980 |           0x4000 |
+|  168 | blk.18.attn_output.weight |       0x8144d980 |         0xb00000 |
+|  169 | blk.18.attn_q.weight      |       0x81f4d980 |         0x6e0000 |
+|  170 | blk.18.attn_v.weight      |       0x8262d980 |         0x240000 |
+|  171 | blk.18.ffn_down.weight    |       0x8286d980 |        0x2680000 |
+|  172 | blk.18.ffn_gate.weight    |       0x84eed980 |        0x1810000 |
+|  173 | blk.18.ffn_norm.weight    |       0x866fd980 |           0x4000 |
+|  174 | blk.18.ffn_up.weight      |       0x86701980 |        0x1810000 |
+|  175 | blk.19.attn_k.weight      |       0x87f11980 |         0x1b8000 |
+|  176 | blk.19.attn_norm.weight   |       0x880c9980 |           0x4000 |
+|  177 | blk.19.attn_output.weight |       0x880cd980 |         0xb00000 |
+|  178 | blk.19.attn_q.weight      |       0x88bcd980 |         0x6e0000 |
+|  179 | blk.19.attn_v.weight      |       0x892ad980 |         0x240000 |
+|  180 | blk.19.ffn_down.weight    |       0x894ed980 |        0x2680000 |
+|  181 | blk.19.ffn_gate.weight    |       0x8bb6d980 |        0x1810000 |
+|  182 | blk.19.ffn_norm.weight    |       0x8d37d980 |           0x4000 |
+|  183 | blk.19.ffn_up.weight      |       0x8d381980 |        0x1810000 |
+|  184 | blk.20.attn_k.weight      |       0x8eb91980 |         0x1b8000 |
+|  185 | blk.20.attn_norm.weight   |       0x8ed49980 |           0x4000 |
+|  186 | blk.20.attn_output.weight |       0x8ed4d980 |         0xb00000 |
+|  187 | blk.20.attn_q.weight      |       0x8f84d980 |         0x6e0000 |
+|  188 | blk.20.attn_v.weight      |       0x8ff2d980 |         0x240000 |
+|  189 | blk.20.ffn_down.weight    |       0x9016d980 |        0x2680000 |
+|  190 | blk.20.ffn_gate.weight    |       0x927ed980 |        0x1810000 |
+|  191 | blk.20.ffn_norm.weight    |       0x93ffd980 |           0x4000 |
+|  192 | blk.20.ffn_up.weight      |       0x94001980 |        0x1810000 |
+|  193 | blk.21.attn_k.weight      |       0x95811980 |         0x1b8000 |
+|  194 | blk.21.attn_norm.weight   |       0x959c9980 |           0x4000 |
+|  195 | blk.21.attn_output.weight |       0x959cd980 |         0xb00000 |
+|  196 | blk.21.attn_q.weight      |       0x964cd980 |         0x6e0000 |
+|  197 | blk.21.attn_v.weight      |       0x96bad980 |         0x240000 |
+|  198 | blk.21.ffn_down.weight    |       0x96ded980 |        0x2680000 |
+|  199 | blk.21.ffn_gate.weight    |       0x9946d980 |        0x1810000 |
+|  200 | blk.21.ffn_norm.weight    |       0x9ac7d980 |           0x4000 |
+|  201 | blk.21.ffn_up.weight      |       0x9ac81980 |        0x1810000 |
+|  202 | blk.22.attn_k.weight      |       0x9c491980 |         0x1b8000 |
+|  203 | blk.22.attn_norm.weight   |       0x9c649980 |           0x4000 |
+|  204 | blk.22.attn_output.weight |       0x9c64d980 |         0xb00000 |
+|  205 | blk.22.attn_q.weight      |       0x9d14d980 |         0x6e0000 |
+|  206 | blk.22.attn_v.weight      |       0x9d82d980 |         0x240000 |
+|  207 | blk.22.ffn_down.weight    |       0x9da6d980 |        0x2680000 |
+|  208 | blk.22.ffn_gate.weight    |       0xa00ed980 |        0x1810000 |
+|  209 | blk.22.ffn_norm.weight    |       0xa18fd980 |           0x4000 |
+|  210 | blk.22.ffn_up.weight      |       0xa1901980 |        0x1810000 |
+|  211 | blk.23.attn_k.weight      |       0xa3111980 |         0x1b8000 |
+|  212 | blk.23.attn_norm.weight   |       0xa32c9980 |           0x4000 |
+|  213 | blk.23.attn_output.weight |       0xa32cd980 |         0xb00000 |
+|  214 | blk.23.attn_q.weight      |       0xa3dcd980 |         0x6e0000 |
+|  215 | blk.23.attn_v.weight      |       0xa44ad980 |         0x240000 |
+|  216 | blk.23.ffn_down.weight    |       0xa46ed980 |        0x2680000 |
+|  217 | blk.23.ffn_gate.weight    |       0xa6d6d980 |        0x1810000 |
+|  218 | blk.23.ffn_norm.weight    |       0xa857d980 |           0x4000 |
+|  219 | blk.23.ffn_up.weight      |       0xa8581980 |        0x1810000 |
+|  220 | blk.24.attn_k.weight      |       0xa9d91980 |         0x1b8000 |
+|  221 | blk.24.attn_norm.weight   |       0xa9f49980 |           0x4000 |
+|  222 | blk.24.attn_output.weight |       0xa9f4d980 |         0xb00000 |
+|  223 | blk.24.attn_q.weight      |       0xaaa4d980 |         0x6e0000 |
+|  224 | blk.24.attn_v.weight      |       0xab12d980 |         0x240000 |
+|  225 | blk.24.ffn_down.weight    |       0xab36d980 |        0x2680000 |
+|  226 | blk.24.ffn_gate.weight    |       0xad9ed980 |        0x1810000 |
+|  227 | blk.24.ffn_norm.weight    |       0xaf1fd980 |           0x4000 |
+|  228 | blk.24.ffn_up.weight      |       0xaf201980 |        0x1810000 |
+|  229 | blk.25.attn_k.weight      |       0xb0a11980 |         0x1b8000 |
+|  230 | blk.25.attn_norm.weight   |       0xb0bc9980 |           0x4000 |
+|  231 | blk.25.attn_output.weight |       0xb0bcd980 |         0xb00000 |
+|  232 | blk.25.attn_q.weight      |       0xb16cd980 |         0x6e0000 |
+|  233 | blk.25.attn_v.weight      |       0xb1dad980 |         0x240000 |
+|  234 | blk.25.ffn_down.weight    |       0xb1fed980 |        0x2680000 |
+|  235 | blk.25.ffn_gate.weight    |       0xb466d980 |        0x1810000 |
+|  236 | blk.25.ffn_norm.weight    |       0xb5e7d980 |           0x4000 |
+|  237 | blk.25.ffn_up.weight      |       0xb5e81980 |        0x1810000 |
+|  238 | blk.26.attn_k.weight      |       0xb7691980 |         0x1b8000 |
+|  239 | blk.26.attn_norm.weight   |       0xb7849980 |           0x4000 |
+|  240 | blk.26.attn_output.weight |       0xb784d980 |         0xb00000 |
+|  241 | blk.26.attn_q.weight      |       0xb834d980 |         0x6e0000 |
+|  242 | blk.26.attn_v.weight      |       0xb8a2d980 |         0x240000 |
+|  243 | blk.26.ffn_down.weight    |       0xb8c6d980 |        0x2680000 |
+|  244 | blk.26.ffn_gate.weight    |       0xbb2ed980 |        0x1810000 |
+|  245 | blk.26.ffn_norm.weight    |       0xbcafd980 |           0x4000 |
+|  246 | blk.26.ffn_up.weight      |       0xbcb01980 |        0x1810000 |
+|  247 | blk.27.attn_k.weight      |       0xbe311980 |         0x1b8000 |
+|  248 | blk.27.attn_norm.weight   |       0xbe4c9980 |           0x4000 |
+|  249 | blk.27.attn_output.weight |       0xbe4cd980 |         0xb00000 |
+|  250 | blk.27.attn_q.weight      |       0xbefcd980 |         0x6e0000 |
+|  251 | blk.27.attn_v.weight      |       0xbf6ad980 |         0x240000 |
+|  252 | blk.27.ffn_down.weight    |       0xbf8ed980 |        0x2680000 |
+|  253 | blk.27.ffn_gate.weight    |       0xc1f6d980 |        0x1810000 |
+|  254 | blk.27.ffn_norm.weight    |       0xc377d980 |           0x4000 |
+|  255 | blk.27.ffn_up.weight      |       0xc3781980 |        0x1810000 |
+|  256 | blk.28.attn_k.weight      |       0xc4f91980 |         0x1b8000 |
+|  257 | blk.28.attn_norm.weight   |       0xc5149980 |           0x4000 |
+|  258 | blk.28.attn_output.weight |       0xc514d980 |         0xb00000 |
+|  259 | blk.28.attn_q.weight      |       0xc5c4d980 |         0x6e0000 |
+|  260 | blk.28.attn_v.weight      |       0xc632d980 |         0x240000 |
+|  261 | blk.28.ffn_down.weight    |       0xc656d980 |        0x2680000 |
+|  262 | blk.28.ffn_gate.weight    |       0xc8bed980 |        0x1810000 |
+|  263 | blk.28.ffn_norm.weight    |       0xca3fd980 |           0x4000 |
+|  264 | blk.28.ffn_up.weight      |       0xca401980 |        0x1810000 |
+|  265 | blk.29.attn_k.weight      |       0xcbc11980 |         0x1b8000 |
+|  266 | blk.29.attn_norm.weight   |       0xcbdc9980 |           0x4000 |
+|  267 | blk.29.attn_output.weight |       0xcbdcd980 |         0xb00000 |
+|  268 | blk.29.attn_q.weight      |       0xcc8cd980 |         0x6e0000 |
+|  269 | blk.29.attn_v.weight      |       0xccfad980 |         0x240000 |
+|  270 | blk.29.ffn_down.weight    |       0xcd1ed980 |        0x2680000 |
+|  271 | blk.29.ffn_gate.weight    |       0xcf86d980 |        0x1810000 |
+|  272 | blk.29.ffn_norm.weight    |       0xd107d980 |           0x4000 |
+|  273 | blk.29.ffn_up.weight      |       0xd1081980 |        0x1810000 |
+|  274 | blk.30.attn_k.weight      |       0xd2891980 |         0x1b8000 |
+|  275 | blk.30.attn_norm.weight   |       0xd2a49980 |           0x4000 |
+|  276 | blk.30.attn_output.weight |       0xd2a4d980 |         0xb00000 |
+|  277 | blk.30.attn_q.weight      |       0xd354d980 |         0x6e0000 |
+|  278 | blk.30.attn_v.weight      |       0xd3c2d980 |         0x240000 |
+|  279 | blk.30.ffn_down.weight    |       0xd3e6d980 |        0x2680000 |
+|  280 | blk.30.ffn_gate.weight    |       0xd64ed980 |        0x1810000 |
+|  281 | blk.30.ffn_norm.weight    |       0xd7cfd980 |           0x4000 |
+|  282 | blk.30.ffn_up.weight      |       0xd7d01980 |        0x1810000 |
+|  283 | blk.31.attn_k.weight      |       0xd9511980 |         0x150000 |
+|  284 | blk.31.attn_norm.weight   |       0xd9661980 |           0x4000 |
+|  285 | blk.31.attn_output.weight |       0xd9665980 |         0xb00000 |
+|  286 | blk.31.attn_q.weight      |       0xda165980 |         0x540000 |
+|  287 | blk.31.attn_v.weight      |       0xda6a5980 |         0x240000 |
+|  288 | blk.31.ffn_down.weight    |       0xda8e5980 |        0x2680000 |
+|  289 | blk.31.ffn_gate.weight    |       0xdcf65980 |        0x1810000 |
+|  290 | blk.31.ffn_norm.weight    |       0xde775980 |           0x4000 |
+|  291 | blk.31.ffn_up.weight      |       0xde779980 |        0x1810000 |
+### <a name="base">Base Tensor Group : ~1B Elements</a>
+| T_ID | Tensor Layer Name  | Human Friendly Tensor Layer Name | Elements          | Shape                 | Type |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
+|    0 | output.weight      | Output (W)                       | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q3_K |
+|    1 | output_norm.weight | Output Normalization (W)         | (  ~4K)      4096 | 4096 x      1 x 1 x 1 | F32  |
+|    2 | rope_freqs.weight  | Rope_Freqs (W)                   | (   64)        64 |   64 x      1 x 1 x 1 | F32  |
+|    3 | token_embd.weight  | Token Embedding (W)              | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q3_K |
+- Total elements in base: ( ~1B) 1050677312
+- Percentage of total elements: 13.08%
+### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|    4 | blk.0.attn_k.weight      | Block 0 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|    5 | blk.0.attn_norm.weight   | Block 0 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|    6 | blk.0.attn_output.weight | Block 0 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|    7 | blk.0.attn_q.weight      | Block 0 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|    8 | blk.0.attn_v.weight      | Block 0 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|    9 | blk.0.ffn_down.weight    | Block 0 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   10 | blk.0.ffn_gate.weight    | Block 0 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   11 | blk.0.ffn_norm.weight    | Block 0 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   12 | blk.0.ffn_up.weight      | Block 0 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.0: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   13 | blk.1.attn_k.weight      | Block 1 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   14 | blk.1.attn_norm.weight   | Block 1 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   15 | blk.1.attn_output.weight | Block 1 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   16 | blk.1.attn_q.weight      | Block 1 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   17 | blk.1.attn_v.weight      | Block 1 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   18 | blk.1.ffn_down.weight    | Block 1 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   19 | blk.1.ffn_gate.weight    | Block 1 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   20 | blk.1.ffn_norm.weight    | Block 1 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   21 | blk.1.ffn_up.weight      | Block 1 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.1: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   22 | blk.2.attn_k.weight      | Block 2 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   23 | blk.2.attn_norm.weight   | Block 2 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   24 | blk.2.attn_output.weight | Block 2 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   25 | blk.2.attn_q.weight      | Block 2 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   26 | blk.2.attn_v.weight      | Block 2 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   27 | blk.2.ffn_down.weight    | Block 2 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   28 | blk.2.ffn_gate.weight    | Block 2 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   29 | blk.2.ffn_norm.weight    | Block 2 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   30 | blk.2.ffn_up.weight      | Block 2 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.2: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   31 | blk.3.attn_k.weight      | Block 3 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   32 | blk.3.attn_norm.weight   | Block 3 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   33 | blk.3.attn_output.weight | Block 3 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   34 | blk.3.attn_q.weight      | Block 3 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   35 | blk.3.attn_v.weight      | Block 3 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   36 | blk.3.ffn_down.weight    | Block 3 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   37 | blk.3.ffn_gate.weight    | Block 3 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   38 | blk.3.ffn_norm.weight    | Block 3 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   39 | blk.3.ffn_up.weight      | Block 3 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.3: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   40 | blk.4.attn_k.weight      | Block 4 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   41 | blk.4.attn_norm.weight   | Block 4 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   42 | blk.4.attn_output.weight | Block 4 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   43 | blk.4.attn_q.weight      | Block 4 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   44 | blk.4.attn_v.weight      | Block 4 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   45 | blk.4.ffn_down.weight    | Block 4 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   46 | blk.4.ffn_gate.weight    | Block 4 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   47 | blk.4.ffn_norm.weight    | Block 4 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   48 | blk.4.ffn_up.weight      | Block 4 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.4: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   49 | blk.5.attn_k.weight      | Block 5 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   50 | blk.5.attn_norm.weight   | Block 5 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   51 | blk.5.attn_output.weight | Block 5 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   52 | blk.5.attn_q.weight      | Block 5 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   53 | blk.5.attn_v.weight      | Block 5 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   54 | blk.5.ffn_down.weight    | Block 5 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   55 | blk.5.ffn_gate.weight    | Block 5 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   56 | blk.5.ffn_norm.weight    | Block 5 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   57 | blk.5.ffn_up.weight      | Block 5 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.5: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   58 | blk.6.attn_k.weight      | Block 6 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   59 | blk.6.attn_norm.weight   | Block 6 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   60 | blk.6.attn_output.weight | Block 6 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   61 | blk.6.attn_q.weight      | Block 6 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   62 | blk.6.attn_v.weight      | Block 6 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   63 | blk.6.ffn_down.weight    | Block 6 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   64 | blk.6.ffn_gate.weight    | Block 6 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   65 | blk.6.ffn_norm.weight    | Block 6 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   66 | blk.6.ffn_up.weight      | Block 6 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.6: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   67 | blk.7.attn_k.weight      | Block 7 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   68 | blk.7.attn_norm.weight   | Block 7 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   69 | blk.7.attn_output.weight | Block 7 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   70 | blk.7.attn_q.weight      | Block 7 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   71 | blk.7.attn_v.weight      | Block 7 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   72 | blk.7.ffn_down.weight    | Block 7 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   73 | blk.7.ffn_gate.weight    | Block 7 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   74 | blk.7.ffn_norm.weight    | Block 7 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   75 | blk.7.ffn_up.weight      | Block 7 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.7: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   76 | blk.8.attn_k.weight      | Block 8 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   77 | blk.8.attn_norm.weight   | Block 8 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   78 | blk.8.attn_output.weight | Block 8 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   79 | blk.8.attn_q.weight      | Block 8 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   80 | blk.8.attn_v.weight      | Block 8 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   81 | blk.8.ffn_down.weight    | Block 8 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   82 | blk.8.ffn_gate.weight    | Block 8 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   83 | blk.8.ffn_norm.weight    | Block 8 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   84 | blk.8.ffn_up.weight      | Block 8 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.8: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   85 | blk.9.attn_k.weight      | Block 9 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   86 | blk.9.attn_norm.weight   | Block 9 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   87 | blk.9.attn_output.weight | Block 9 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   88 | blk.9.attn_q.weight      | Block 9 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   89 | blk.9.attn_v.weight      | Block 9 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   90 | blk.9.ffn_down.weight    | Block 9 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   91 | blk.9.ffn_gate.weight    | Block 9 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   92 | blk.9.ffn_norm.weight    | Block 9 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   93 | blk.9.ffn_up.weight      | Block 9 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.9: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|   94 | blk.10.attn_k.weight      | Block 10 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   95 | blk.10.attn_norm.weight   | Block 10 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   96 | blk.10.attn_output.weight | Block 10 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   97 | blk.10.attn_q.weight      | Block 10 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   98 | blk.10.attn_v.weight      | Block 10 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   99 | blk.10.ffn_down.weight    | Block 10 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  100 | blk.10.ffn_gate.weight    | Block 10 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  101 | blk.10.ffn_norm.weight    | Block 10 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  102 | blk.10.ffn_up.weight      | Block 10 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.10: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  103 | blk.11.attn_k.weight      | Block 11 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  104 | blk.11.attn_norm.weight   | Block 11 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  105 | blk.11.attn_output.weight | Block 11 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  106 | blk.11.attn_q.weight      | Block 11 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  107 | blk.11.attn_v.weight      | Block 11 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  108 | blk.11.ffn_down.weight    | Block 11 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  109 | blk.11.ffn_gate.weight    | Block 11 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  110 | blk.11.ffn_norm.weight    | Block 11 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  111 | blk.11.ffn_up.weight      | Block 11 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.11: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  112 | blk.12.attn_k.weight      | Block 12 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  113 | blk.12.attn_norm.weight   | Block 12 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  114 | blk.12.attn_output.weight | Block 12 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  115 | blk.12.attn_q.weight      | Block 12 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  116 | blk.12.attn_v.weight      | Block 12 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  117 | blk.12.ffn_down.weight    | Block 12 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  118 | blk.12.ffn_gate.weight    | Block 12 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  119 | blk.12.ffn_norm.weight    | Block 12 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  120 | blk.12.ffn_up.weight      | Block 12 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.12: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  121 | blk.13.attn_k.weight      | Block 13 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  122 | blk.13.attn_norm.weight   | Block 13 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  123 | blk.13.attn_output.weight | Block 13 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  124 | blk.13.attn_q.weight      | Block 13 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  125 | blk.13.attn_v.weight      | Block 13 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  126 | blk.13.ffn_down.weight    | Block 13 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  127 | blk.13.ffn_gate.weight    | Block 13 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  128 | blk.13.ffn_norm.weight    | Block 13 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  129 | blk.13.ffn_up.weight      | Block 13 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.13: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  130 | blk.14.attn_k.weight      | Block 14 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  131 | blk.14.attn_norm.weight   | Block 14 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  132 | blk.14.attn_output.weight | Block 14 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  133 | blk.14.attn_q.weight      | Block 14 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  134 | blk.14.attn_v.weight      | Block 14 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  135 | blk.14.ffn_down.weight    | Block 14 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  136 | blk.14.ffn_gate.weight    | Block 14 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  137 | blk.14.ffn_norm.weight    | Block 14 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  138 | blk.14.ffn_up.weight      | Block 14 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.14: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  139 | blk.15.attn_k.weight      | Block 15 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  140 | blk.15.attn_norm.weight   | Block 15 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  141 | blk.15.attn_output.weight | Block 15 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  142 | blk.15.attn_q.weight      | Block 15 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  143 | blk.15.attn_v.weight      | Block 15 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  144 | blk.15.ffn_down.weight    | Block 15 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  145 | blk.15.ffn_gate.weight    | Block 15 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  146 | blk.15.ffn_norm.weight    | Block 15 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  147 | blk.15.ffn_up.weight      | Block 15 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.15: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  148 | blk.16.attn_k.weight      | Block 16 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  149 | blk.16.attn_norm.weight   | Block 16 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  150 | blk.16.attn_output.weight | Block 16 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  151 | blk.16.attn_q.weight      | Block 16 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  152 | blk.16.attn_v.weight      | Block 16 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  153 | blk.16.ffn_down.weight    | Block 16 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  154 | blk.16.ffn_gate.weight    | Block 16 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  155 | blk.16.ffn_norm.weight    | Block 16 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  156 | blk.16.ffn_up.weight      | Block 16 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.16: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  157 | blk.17.attn_k.weight      | Block 17 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  158 | blk.17.attn_norm.weight   | Block 17 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  159 | blk.17.attn_output.weight | Block 17 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  160 | blk.17.attn_q.weight      | Block 17 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  161 | blk.17.attn_v.weight      | Block 17 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  162 | blk.17.ffn_down.weight    | Block 17 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  163 | blk.17.ffn_gate.weight    | Block 17 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  164 | blk.17.ffn_norm.weight    | Block 17 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  165 | blk.17.ffn_up.weight      | Block 17 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.17: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  166 | blk.18.attn_k.weight      | Block 18 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  167 | blk.18.attn_norm.weight   | Block 18 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  168 | blk.18.attn_output.weight | Block 18 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  169 | blk.18.attn_q.weight      | Block 18 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  170 | blk.18.attn_v.weight      | Block 18 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  171 | blk.18.ffn_down.weight    | Block 18 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  172 | blk.18.ffn_gate.weight    | Block 18 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  173 | blk.18.ffn_norm.weight    | Block 18 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  174 | blk.18.ffn_up.weight      | Block 18 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.18: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  175 | blk.19.attn_k.weight      | Block 19 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  176 | blk.19.attn_norm.weight   | Block 19 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  177 | blk.19.attn_output.weight | Block 19 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  178 | blk.19.attn_q.weight      | Block 19 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  179 | blk.19.attn_v.weight      | Block 19 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  180 | blk.19.ffn_down.weight    | Block 19 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  181 | blk.19.ffn_gate.weight    | Block 19 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  182 | blk.19.ffn_norm.weight    | Block 19 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  183 | blk.19.ffn_up.weight      | Block 19 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.19: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  184 | blk.20.attn_k.weight      | Block 20 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  185 | blk.20.attn_norm.weight   | Block 20 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  186 | blk.20.attn_output.weight | Block 20 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  187 | blk.20.attn_q.weight      | Block 20 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  188 | blk.20.attn_v.weight      | Block 20 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  189 | blk.20.ffn_down.weight    | Block 20 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  190 | blk.20.ffn_gate.weight    | Block 20 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  191 | blk.20.ffn_norm.weight    | Block 20 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  192 | blk.20.ffn_up.weight      | Block 20 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.20: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  193 | blk.21.attn_k.weight      | Block 21 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  194 | blk.21.attn_norm.weight   | Block 21 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  195 | blk.21.attn_output.weight | Block 21 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  196 | blk.21.attn_q.weight      | Block 21 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  197 | blk.21.attn_v.weight      | Block 21 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  198 | blk.21.ffn_down.weight    | Block 21 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  199 | blk.21.ffn_gate.weight    | Block 21 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  200 | blk.21.ffn_norm.weight    | Block 21 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  201 | blk.21.ffn_up.weight      | Block 21 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.21: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  202 | blk.22.attn_k.weight      | Block 22 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  203 | blk.22.attn_norm.weight   | Block 22 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  204 | blk.22.attn_output.weight | Block 22 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  205 | blk.22.attn_q.weight      | Block 22 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  206 | blk.22.attn_v.weight      | Block 22 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  207 | blk.22.ffn_down.weight    | Block 22 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  208 | blk.22.ffn_gate.weight    | Block 22 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  209 | blk.22.ffn_norm.weight    | Block 22 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  210 | blk.22.ffn_up.weight      | Block 22 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.22: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  211 | blk.23.attn_k.weight      | Block 23 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  212 | blk.23.attn_norm.weight   | Block 23 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  213 | blk.23.attn_output.weight | Block 23 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  214 | blk.23.attn_q.weight      | Block 23 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  215 | blk.23.attn_v.weight      | Block 23 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  216 | blk.23.ffn_down.weight    | Block 23 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  217 | blk.23.ffn_gate.weight    | Block 23 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  218 | blk.23.ffn_norm.weight    | Block 23 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  219 | blk.23.ffn_up.weight      | Block 23 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.23: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  220 | blk.24.attn_k.weight      | Block 24 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  221 | blk.24.attn_norm.weight   | Block 24 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  222 | blk.24.attn_output.weight | Block 24 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  223 | blk.24.attn_q.weight      | Block 24 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  224 | blk.24.attn_v.weight      | Block 24 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  225 | blk.24.ffn_down.weight    | Block 24 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  226 | blk.24.ffn_gate.weight    | Block 24 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  227 | blk.24.ffn_norm.weight    | Block 24 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  228 | blk.24.ffn_up.weight      | Block 24 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.24: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  229 | blk.25.attn_k.weight      | Block 25 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  230 | blk.25.attn_norm.weight   | Block 25 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  231 | blk.25.attn_output.weight | Block 25 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  232 | blk.25.attn_q.weight      | Block 25 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  233 | blk.25.attn_v.weight      | Block 25 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  234 | blk.25.ffn_down.weight    | Block 25 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  235 | blk.25.ffn_gate.weight    | Block 25 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  236 | blk.25.ffn_norm.weight    | Block 25 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  237 | blk.25.ffn_up.weight      | Block 25 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.25: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  238 | blk.26.attn_k.weight      | Block 26 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  239 | blk.26.attn_norm.weight   | Block 26 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  240 | blk.26.attn_output.weight | Block 26 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  241 | blk.26.attn_q.weight      | Block 26 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  242 | blk.26.attn_v.weight      | Block 26 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  243 | blk.26.ffn_down.weight    | Block 26 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  244 | blk.26.ffn_gate.weight    | Block 26 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  245 | blk.26.ffn_norm.weight    | Block 26 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  246 | blk.26.ffn_up.weight      | Block 26 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.26: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  247 | blk.27.attn_k.weight      | Block 27 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  248 | blk.27.attn_norm.weight   | Block 27 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  249 | blk.27.attn_output.weight | Block 27 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  250 | blk.27.attn_q.weight      | Block 27 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  251 | blk.27.attn_v.weight      | Block 27 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  252 | blk.27.ffn_down.weight    | Block 27 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  253 | blk.27.ffn_gate.weight    | Block 27 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  254 | blk.27.ffn_norm.weight    | Block 27 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  255 | blk.27.ffn_up.weight      | Block 27 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.27: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  256 | blk.28.attn_k.weight      | Block 28 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  257 | blk.28.attn_norm.weight   | Block 28 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  258 | blk.28.attn_output.weight | Block 28 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  259 | blk.28.attn_q.weight      | Block 28 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  260 | blk.28.attn_v.weight      | Block 28 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  261 | blk.28.ffn_down.weight    | Block 28 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  262 | blk.28.ffn_gate.weight    | Block 28 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  263 | blk.28.ffn_norm.weight    | Block 28 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  264 | blk.28.ffn_up.weight      | Block 28 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.28: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  265 | blk.29.attn_k.weight      | Block 29 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  266 | blk.29.attn_norm.weight   | Block 29 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  267 | blk.29.attn_output.weight | Block 29 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  268 | blk.29.attn_q.weight      | Block 29 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  269 | blk.29.attn_v.weight      | Block 29 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  270 | blk.29.ffn_down.weight    | Block 29 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  271 | blk.29.ffn_gate.weight    | Block 29 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  272 | blk.29.ffn_norm.weight    | Block 29 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  273 | blk.29.ffn_up.weight      | Block 29 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.29: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  274 | blk.30.attn_k.weight      | Block 30 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  275 | blk.30.attn_norm.weight   | Block 30 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  276 | blk.30.attn_output.weight | Block 30 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  277 | blk.30.attn_q.weight      | Block 30 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  278 | blk.30.attn_v.weight      | Block 30 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  279 | blk.30.ffn_down.weight    | Block 30 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  280 | blk.30.ffn_gate.weight    | Block 30 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  281 | blk.30.ffn_norm.weight    | Block 30 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  282 | blk.30.ffn_up.weight      | Block 30 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.30: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  283 | blk.31.attn_k.weight      | Block 31 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  284 | blk.31.attn_norm.weight   | Block 31 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  285 | blk.31.attn_output.weight | Block 31 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  286 | blk.31.attn_q.weight      | Block 31 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  287 | blk.31.attn_v.weight      | Block 31 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  288 | blk.31.ffn_down.weight    | Block 31 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  289 | blk.31.ffn_gate.weight    | Block 31 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  290 | blk.31.ffn_norm.weight    | Block 31 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  291 | blk.31.ffn_up.weight      | Block 31 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.31: (~218M) 218112000
+- Percentage of total elements: 2.72%

scores/Llama-Guard-3-8B-Q3_K_M.md ADDED Viewed

	@@ -0,0 +1,978 @@

+# Llama-Guard-3-8B-Q3_K_M.gguf - GGUF Internal File Dump
+- Endian: LITTLE endian
+## Key Value Metadata Store
+There are 39 key-value pairs in this file
+| POS | TYPE     |  Count | Key                                    | Value                                                               |
+|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
+|   1 | UINT32   |      1 | GGUF.version                           | 3                                                                   |
+|   2 | UINT64   |      1 | GGUF.tensor_count                      | 292                                                                 |
+|   3 | UINT64   |      1 | GGUF.kv_count                          | 36                                                                  |
+|   4 | STRING   |      1 | general.architecture                   | `llama`                                                             |
+|   5 | STRING   |      1 | general.type                           | `model`                                                             |
+|   6 | STRING   |      1 | general.name                           | `Llama Guard 3 8B`                                                  |
+|   7 | STRING   |      1 | general.basename                       | `Llama-Guard-3`                                                     |
+|   8 | STRING   |      1 | general.size_label                     | `8B`                                                                |
+|   9 | STRING   |      1 | general.license                        | `llama3.1`                                                          |
+|  10 | UINT32   |      1 | general.base_model.count               | 1                                                                   |
+|  11 | STRING   |      1 | general.base_model.0.name              | `Meta Llama 3.1 8B`                                                 |
+|  12 | STRING   |      1 | general.base_model.0.organization      | `Meta Llama`                                                        |
+|  13 | STRING   |      1 | general.base_model.0.repo_url          | `https://huggingface.co/meta-llama/Meta-Llama-3.1-8B`               |
+|  14 | [STRING] |      6 | general.tags                           | [ `facebook`, `meta`, `pytorch`, `llama`, `llama-3`, ... ]          |
+|  15 | [STRING] |      1 | general.languages                      | [ `en` ]                                                            |
+|  16 | UINT32   |      1 | llama.block_count                      | 32                                                                  |
+|  17 | UINT32   |      1 | llama.context_length                   | 131072                                                              |
+|  18 | UINT32   |      1 | llama.embedding_length                 | 4096                                                                |
+|  19 | UINT32   |      1 | llama.feed_forward_length              | 14336                                                               |
+|  20 | UINT32   |      1 | llama.attention.head_count             | 32                                                                  |
+|  21 | UINT32   |      1 | llama.attention.head_count_kv          | 8                                                                   |
+|  22 | FLOAT32  |      1 | llama.rope.freq_base                   | 500000.0                                                            |
+|  23 | FLOAT32  |      1 | llama.attention.layer_norm_rms_epsilon | 1e-05                                                               |
+|  24 | UINT32   |      1 | llama.vocab_size                       | 128256                                                              |
+|  25 | UINT32   |      1 | llama.rope.dimension_count             | 128                                                                 |
+|  26 | STRING   |      1 | tokenizer.ggml.model                   | `gpt2`                                                              |
+|  27 | STRING   |      1 | tokenizer.ggml.pre                     | `smaug-bpe`                                                         |
+|  28 | [STRING] | 128256 | tokenizer.ggml.tokens                  | [ `!`, `"`, `#`, `$`, `%`, ... ]                                    |
+|  29 | [INT32]  | 128256 | tokenizer.ggml.token_type              | [ 1, 1, 1, 1, 1, 1, 1, ... ]                                        |
+|  30 | [STRING] | 280147 | tokenizer.ggml.merges                  | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]                    |
+|  31 | UINT32   |      1 | tokenizer.ggml.bos_token_id            | 128000                                                              |
+|  32 | UINT32   |      1 | tokenizer.ggml.eos_token_id            | 128009                                                              |
+|  33 | STRING   |      1 | tokenizer.chat_template                | `{% if messages|length % 2 == 0`...`assistant<|end_header_id|>" }}` |
+|  34 | UINT32   |      1 | general.quantization_version           | 2                                                                   |
+|  35 | UINT32   |      1 | general.file_type                      | 12                                                                  |
+|  36 | STRING   |      1 | quantize.imatrix.file                  | `./imatrix/imatrix-Llama-Guard-3-8B-small.dat`                      |
+|  37 | STRING   |      1 | quantize.imatrix.dataset               | `../../datasets/imatrix/calibration_eur_small.txt`                  |
+|  38 | INT32    |      1 | quantize.imatrix.entries_count         | 224                                                                 |
+|  39 | INT32    |      1 | quantize.imatrix.chunks_count          | 962                                                                 |
+## Tensors Overview ~8B Elements
+Total number of elements in all tensors: 8030261312 Elements
+- [Llama-Guard-3-8B-Q3\_K\_M.gguf - GGUF Internal File Dump](#llama-guard-3-8b-q3_k_mgguf---gguf-internal-file-dump)
+  - [Key Value Metadata Store](#key-value-metadata-store)
+  - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
+    - [Tensor Data Offset](#tensor-data-offset)
+    - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
+    - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
+    - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
+    - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
+    - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
+    - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
+    - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
+    - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
+    - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
+    - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
+    - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
+    - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
+    - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
+    - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
+    - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
+    - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
+    - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
+    - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
+    - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
+    - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
+    - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
+    - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
+    - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
+    - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
+    - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
+    - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
+    - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
+    - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
+    - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
+    - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
+    - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
+    - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
+    - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
+### Tensor Data Offset
+This table contains the offset and data segment relative to start of file
+| T_ID | Tensor Layer Name         |  Data Offset (B) |    Data Size (B) |
+|-----:|:--------------------------|-----------------:|-----------------:|
+|    0 | output.weight             |         0x779880 |        0xd746000 |
+|    1 | output_norm.weight        |        0xdebf880 |           0x4000 |
+|    2 | rope_freqs.weight         |        0xdec3880 |            0x100 |
+|    3 | token_embd.weight         |        0xdec3980 |        0xd746000 |
+|    4 | blk.0.attn_k.weight       |       0x1b609980 |         0x150000 |
+|    5 | blk.0.attn_norm.weight    |       0x1b759980 |           0x4000 |
+|    6 | blk.0.attn_output.weight  |       0x1b75d980 |         0x900000 |
+|    7 | blk.0.attn_q.weight       |       0x1c05d980 |         0x540000 |
+|    8 | blk.0.attn_v.weight       |       0x1c59d980 |         0x1b8000 |
+|    9 | blk.0.ffn_down.weight     |       0x1c755980 |        0x1f80000 |
+|   10 | blk.0.ffn_gate.weight     |       0x1e6d5980 |        0x1260000 |
+|   11 | blk.0.ffn_norm.weight     |       0x1f935980 |           0x4000 |
+|   12 | blk.0.ffn_up.weight       |       0x1f939980 |        0x1260000 |
+|   13 | blk.1.attn_k.weight       |       0x20b99980 |         0x150000 |
+|   14 | blk.1.attn_norm.weight    |       0x20ce9980 |           0x4000 |
+|   15 | blk.1.attn_output.weight  |       0x20ced980 |         0x900000 |
+|   16 | blk.1.attn_q.weight       |       0x215ed980 |         0x540000 |
+|   17 | blk.1.attn_v.weight       |       0x21b2d980 |         0x1b8000 |
+|   18 | blk.1.ffn_down.weight     |       0x21ce5980 |        0x1f80000 |
+|   19 | blk.1.ffn_gate.weight     |       0x23c65980 |        0x1260000 |
+|   20 | blk.1.ffn_norm.weight     |       0x24ec5980 |           0x4000 |
+|   21 | blk.1.ffn_up.weight       |       0x24ec9980 |        0x1260000 |
+|   22 | blk.2.attn_k.weight       |       0x26129980 |         0x150000 |
+|   23 | blk.2.attn_norm.weight    |       0x26279980 |           0x4000 |
+|   24 | blk.2.attn_output.weight  |       0x2627d980 |         0x900000 |
+|   25 | blk.2.attn_q.weight       |       0x26b7d980 |         0x540000 |
+|   26 | blk.2.attn_v.weight       |       0x270bd980 |         0x1b8000 |
+|   27 | blk.2.ffn_down.weight     |       0x27275980 |        0x1f80000 |
+|   28 | blk.2.ffn_gate.weight     |       0x291f5980 |        0x1260000 |
+|   29 | blk.2.ffn_norm.weight     |       0x2a455980 |           0x4000 |
+|   30 | blk.2.ffn_up.weight       |       0x2a459980 |        0x1260000 |
+|   31 | blk.3.attn_k.weight       |       0x2b6b9980 |         0x150000 |
+|   32 | blk.3.attn_norm.weight    |       0x2b809980 |           0x4000 |
+|   33 | blk.3.attn_output.weight  |       0x2b80d980 |         0x900000 |
+|   34 | blk.3.attn_q.weight       |       0x2c10d980 |         0x540000 |
+|   35 | blk.3.attn_v.weight       |       0x2c64d980 |         0x1b8000 |
+|   36 | blk.3.ffn_down.weight     |       0x2c805980 |        0x1f80000 |
+|   37 | blk.3.ffn_gate.weight     |       0x2e785980 |        0x1260000 |
+|   38 | blk.3.ffn_norm.weight     |       0x2f9e5980 |           0x4000 |
+|   39 | blk.3.ffn_up.weight       |       0x2f9e9980 |        0x1260000 |
+|   40 | blk.4.attn_k.weight       |       0x30c49980 |         0x150000 |
+|   41 | blk.4.attn_norm.weight    |       0x30d99980 |           0x4000 |
+|   42 | blk.4.attn_output.weight  |       0x30d9d980 |         0x900000 |
+|   43 | blk.4.attn_q.weight       |       0x3169d980 |         0x540000 |
+|   44 | blk.4.attn_v.weight       |       0x31bdd980 |         0x1b8000 |
+|   45 | blk.4.ffn_down.weight     |       0x31d95980 |        0x1f80000 |
+|   46 | blk.4.ffn_gate.weight     |       0x33d15980 |        0x1260000 |
+|   47 | blk.4.ffn_norm.weight     |       0x34f75980 |           0x4000 |
+|   48 | blk.4.ffn_up.weight       |       0x34f79980 |        0x1260000 |
+|   49 | blk.5.attn_k.weight       |       0x361d9980 |         0x150000 |
+|   50 | blk.5.attn_norm.weight    |       0x36329980 |           0x4000 |
+|   51 | blk.5.attn_output.weight  |       0x3632d980 |         0x900000 |
+|   52 | blk.5.attn_q.weight       |       0x36c2d980 |         0x540000 |
+|   53 | blk.5.attn_v.weight       |       0x3716d980 |         0x1b8000 |
+|   54 | blk.5.ffn_down.weight     |       0x37325980 |        0x1f80000 |
+|   55 | blk.5.ffn_gate.weight     |       0x392a5980 |        0x1260000 |
+|   56 | blk.5.ffn_norm.weight     |       0x3a505980 |           0x4000 |
+|   57 | blk.5.ffn_up.weight       |       0x3a509980 |        0x1260000 |
+|   58 | blk.6.attn_k.weight       |       0x3b769980 |         0x150000 |
+|   59 | blk.6.attn_norm.weight    |       0x3b8b9980 |           0x4000 |
+|   60 | blk.6.attn_output.weight  |       0x3b8bd980 |         0x900000 |
+|   61 | blk.6.attn_q.weight       |       0x3c1bd980 |         0x540000 |
+|   62 | blk.6.attn_v.weight       |       0x3c6fd980 |         0x1b8000 |
+|   63 | blk.6.ffn_down.weight     |       0x3c8b5980 |        0x1f80000 |
+|   64 | blk.6.ffn_gate.weight     |       0x3e835980 |        0x1260000 |
+|   65 | blk.6.ffn_norm.weight     |       0x3fa95980 |           0x4000 |
+|   66 | blk.6.ffn_up.weight       |       0x3fa99980 |        0x1260000 |
+|   67 | blk.7.attn_k.weight       |       0x40cf9980 |         0x150000 |
+|   68 | blk.7.attn_norm.weight    |       0x40e49980 |           0x4000 |
+|   69 | blk.7.attn_output.weight  |       0x40e4d980 |         0x900000 |
+|   70 | blk.7.attn_q.weight       |       0x4174d980 |         0x540000 |
+|   71 | blk.7.attn_v.weight       |       0x41c8d980 |         0x1b8000 |
+|   72 | blk.7.ffn_down.weight     |       0x41e45980 |        0x1f80000 |
+|   73 | blk.7.ffn_gate.weight     |       0x43dc5980 |        0x1260000 |
+|   74 | blk.7.ffn_norm.weight     |       0x45025980 |           0x4000 |
+|   75 | blk.7.ffn_up.weight       |       0x45029980 |        0x1260000 |
+|   76 | blk.8.attn_k.weight       |       0x46289980 |         0x150000 |
+|   77 | blk.8.attn_norm.weight    |       0x463d9980 |           0x4000 |
+|   78 | blk.8.attn_output.weight  |       0x463dd980 |         0x900000 |
+|   79 | blk.8.attn_q.weight       |       0x46cdd980 |         0x540000 |
+|   80 | blk.8.attn_v.weight       |       0x4721d980 |         0x1b8000 |
+|   81 | blk.8.ffn_down.weight     |       0x473d5980 |        0x1f80000 |
+|   82 | blk.8.ffn_gate.weight     |       0x49355980 |        0x1260000 |
+|   83 | blk.8.ffn_norm.weight     |       0x4a5b5980 |           0x4000 |
+|   84 | blk.8.ffn_up.weight       |       0x4a5b9980 |        0x1260000 |
+|   85 | blk.9.attn_k.weight       |       0x4b819980 |         0x150000 |
+|   86 | blk.9.attn_norm.weight    |       0x4b969980 |           0x4000 |
+|   87 | blk.9.attn_output.weight  |       0x4b96d980 |         0x900000 |
+|   88 | blk.9.attn_q.weight       |       0x4c26d980 |         0x540000 |
+|   89 | blk.9.attn_v.weight       |       0x4c7ad980 |         0x1b8000 |
+|   90 | blk.9.ffn_down.weight     |       0x4c965980 |        0x1f80000 |
+|   91 | blk.9.ffn_gate.weight     |       0x4e8e5980 |        0x1260000 |
+|   92 | blk.9.ffn_norm.weight     |       0x4fb45980 |           0x4000 |
+|   93 | blk.9.ffn_up.weight       |       0x4fb49980 |        0x1260000 |
+|   94 | blk.10.attn_k.weight      |       0x50da9980 |         0x150000 |
+|   95 | blk.10.attn_norm.weight   |       0x50ef9980 |           0x4000 |
+|   96 | blk.10.attn_output.weight |       0x50efd980 |         0x900000 |
+|   97 | blk.10.attn_q.weight      |       0x517fd980 |         0x540000 |
+|   98 | blk.10.attn_v.weight      |       0x51d3d980 |         0x1b8000 |
+|   99 | blk.10.ffn_down.weight    |       0x51ef5980 |        0x1f80000 |
+|  100 | blk.10.ffn_gate.weight    |       0x53e75980 |        0x1260000 |
+|  101 | blk.10.ffn_norm.weight    |       0x550d5980 |           0x4000 |
+|  102 | blk.10.ffn_up.weight      |       0x550d9980 |        0x1260000 |
+|  103 | blk.11.attn_k.weight      |       0x56339980 |         0x150000 |
+|  104 | blk.11.attn_norm.weight   |       0x56489980 |           0x4000 |
+|  105 | blk.11.attn_output.weight |       0x5648d980 |         0x900000 |
+|  106 | blk.11.attn_q.weight      |       0x56d8d980 |         0x540000 |
+|  107 | blk.11.attn_v.weight      |       0x572cd980 |         0x1b8000 |
+|  108 | blk.11.ffn_down.weight    |       0x57485980 |        0x1f80000 |
+|  109 | blk.11.ffn_gate.weight    |       0x59405980 |        0x1260000 |
+|  110 | blk.11.ffn_norm.weight    |       0x5a665980 |           0x4000 |
+|  111 | blk.11.ffn_up.weight      |       0x5a669980 |        0x1260000 |
+|  112 | blk.12.attn_k.weight      |       0x5b8c9980 |         0x150000 |
+|  113 | blk.12.attn_norm.weight   |       0x5ba19980 |           0x4000 |
+|  114 | blk.12.attn_output.weight |       0x5ba1d980 |         0x900000 |
+|  115 | blk.12.attn_q.weight      |       0x5c31d980 |         0x540000 |
+|  116 | blk.12.attn_v.weight      |       0x5c85d980 |         0x1b8000 |
+|  117 | blk.12.ffn_down.weight    |       0x5ca15980 |        0x1f80000 |
+|  118 | blk.12.ffn_gate.weight    |       0x5e995980 |        0x1260000 |
+|  119 | blk.12.ffn_norm.weight    |       0x5fbf5980 |           0x4000 |
+|  120 | blk.12.ffn_up.weight      |       0x5fbf9980 |        0x1260000 |
+|  121 | blk.13.attn_k.weight      |       0x60e59980 |         0x1b8000 |
+|  122 | blk.13.attn_norm.weight   |       0x61011980 |           0x4000 |
+|  123 | blk.13.attn_output.weight |       0x61015980 |         0x900000 |
+|  124 | blk.13.attn_q.weight      |       0x61915980 |         0x6e0000 |
+|  125 | blk.13.attn_v.weight      |       0x61ff5980 |         0x240000 |
+|  126 | blk.13.ffn_down.weight    |       0x62235980 |        0x1f80000 |
+|  127 | blk.13.ffn_gate.weight    |       0x641b5980 |        0x1260000 |
+|  128 | blk.13.ffn_norm.weight    |       0x65415980 |           0x4000 |
+|  129 | blk.13.ffn_up.weight      |       0x65419980 |        0x1260000 |
+|  130 | blk.14.attn_k.weight      |       0x66679980 |         0x1b8000 |
+|  131 | blk.14.attn_norm.weight   |       0x66831980 |           0x4000 |
+|  132 | blk.14.attn_output.weight |       0x66835980 |         0x900000 |
+|  133 | blk.14.attn_q.weight      |       0x67135980 |         0x6e0000 |
+|  134 | blk.14.attn_v.weight      |       0x67815980 |         0x240000 |
+|  135 | blk.14.ffn_down.weight    |       0x67a55980 |        0x1f80000 |
+|  136 | blk.14.ffn_gate.weight    |       0x699d5980 |        0x1260000 |
+|  137 | blk.14.ffn_norm.weight    |       0x6ac35980 |           0x4000 |
+|  138 | blk.14.ffn_up.weight      |       0x6ac39980 |        0x1260000 |
+|  139 | blk.15.attn_k.weight      |       0x6be99980 |         0x150000 |
+|  140 | blk.15.attn_norm.weight   |       0x6bfe9980 |           0x4000 |
+|  141 | blk.15.attn_output.weight |       0x6bfed980 |         0x900000 |
+|  142 | blk.15.attn_q.weight      |       0x6c8ed980 |         0x540000 |
+|  143 | blk.15.attn_v.weight      |       0x6ce2d980 |         0x1b8000 |
+|  144 | blk.15.ffn_down.weight    |       0x6cfe5980 |        0x1f80000 |
+|  145 | blk.15.ffn_gate.weight    |       0x6ef65980 |        0x1260000 |
+|  146 | blk.15.ffn_norm.weight    |       0x701c5980 |           0x4000 |
+|  147 | blk.15.ffn_up.weight      |       0x701c9980 |        0x1260000 |
+|  148 | blk.16.attn_k.weight      |       0x71429980 |         0x1b8000 |
+|  149 | blk.16.attn_norm.weight   |       0x715e1980 |           0x4000 |
+|  150 | blk.16.attn_output.weight |       0x715e5980 |         0x900000 |
+|  151 | blk.16.attn_q.weight      |       0x71ee5980 |         0x6e0000 |
+|  152 | blk.16.attn_v.weight      |       0x725c5980 |         0x240000 |
+|  153 | blk.16.ffn_down.weight    |       0x72805980 |        0x1f80000 |
+|  154 | blk.16.ffn_gate.weight    |       0x74785980 |        0x1810000 |
+|  155 | blk.16.ffn_norm.weight    |       0x75f95980 |           0x4000 |
+|  156 | blk.16.ffn_up.weight      |       0x75f99980 |        0x1810000 |
+|  157 | blk.17.attn_k.weight      |       0x777a9980 |         0x150000 |
+|  158 | blk.17.attn_norm.weight   |       0x778f9980 |           0x4000 |
+|  159 | blk.17.attn_output.weight |       0x778fd980 |         0x900000 |
+|  160 | blk.17.attn_q.weight      |       0x781fd980 |         0x540000 |
+|  161 | blk.17.attn_v.weight      |       0x7873d980 |         0x1b8000 |
+|  162 | blk.17.ffn_down.weight    |       0x788f5980 |        0x1f80000 |
+|  163 | blk.17.ffn_gate.weight    |       0x7a875980 |        0x1810000 |
+|  164 | blk.17.ffn_norm.weight    |       0x7c085980 |           0x4000 |
+|  165 | blk.17.ffn_up.weight      |       0x7c089980 |        0x1810000 |
+|  166 | blk.18.attn_k.weight      |       0x7d899980 |         0x1b8000 |
+|  167 | blk.18.attn_norm.weight   |       0x7da51980 |           0x4000 |
+|  168 | blk.18.attn_output.weight |       0x7da55980 |         0x900000 |
+|  169 | blk.18.attn_q.weight      |       0x7e355980 |         0x6e0000 |
+|  170 | blk.18.attn_v.weight      |       0x7ea35980 |         0x240000 |
+|  171 | blk.18.ffn_down.weight    |       0x7ec75980 |        0x1f80000 |
+|  172 | blk.18.ffn_gate.weight    |       0x80bf5980 |        0x1810000 |
+|  173 | blk.18.ffn_norm.weight    |       0x82405980 |           0x4000 |
+|  174 | blk.18.ffn_up.weight      |       0x82409980 |        0x1810000 |
+|  175 | blk.19.attn_k.weight      |       0x83c19980 |         0x1b8000 |
+|  176 | blk.19.attn_norm.weight   |       0x83dd1980 |           0x4000 |
+|  177 | blk.19.attn_output.weight |       0x83dd5980 |         0x900000 |
+|  178 | blk.19.attn_q.weight      |       0x846d5980 |         0x6e0000 |
+|  179 | blk.19.attn_v.weight      |       0x84db5980 |         0x240000 |
+|  180 | blk.19.ffn_down.weight    |       0x84ff5980 |        0x1f80000 |
+|  181 | blk.19.ffn_gate.weight    |       0x86f75980 |        0x1810000 |
+|  182 | blk.19.ffn_norm.weight    |       0x88785980 |           0x4000 |
+|  183 | blk.19.ffn_up.weight      |       0x88789980 |        0x1810000 |
+|  184 | blk.20.attn_k.weight      |       0x89f99980 |         0x1b8000 |
+|  185 | blk.20.attn_norm.weight   |       0x8a151980 |           0x4000 |
+|  186 | blk.20.attn_output.weight |       0x8a155980 |         0x900000 |
+|  187 | blk.20.attn_q.weight      |       0x8aa55980 |         0x6e0000 |
+|  188 | blk.20.attn_v.weight      |       0x8b135980 |         0x240000 |
+|  189 | blk.20.ffn_down.weight    |       0x8b375980 |        0x1f80000 |
+|  190 | blk.20.ffn_gate.weight    |       0x8d2f5980 |        0x1810000 |
+|  191 | blk.20.ffn_norm.weight    |       0x8eb05980 |           0x4000 |
+|  192 | blk.20.ffn_up.weight      |       0x8eb09980 |        0x1810000 |
+|  193 | blk.21.attn_k.weight      |       0x90319980 |         0x1b8000 |
+|  194 | blk.21.attn_norm.weight   |       0x904d1980 |           0x4000 |
+|  195 | blk.21.attn_output.weight |       0x904d5980 |         0x900000 |
+|  196 | blk.21.attn_q.weight      |       0x90dd5980 |         0x6e0000 |
+|  197 | blk.21.attn_v.weight      |       0x914b5980 |         0x240000 |
+|  198 | blk.21.ffn_down.weight    |       0x916f5980 |        0x1f80000 |
+|  199 | blk.21.ffn_gate.weight    |       0x93675980 |        0x1810000 |
+|  200 | blk.21.ffn_norm.weight    |       0x94e85980 |           0x4000 |
+|  201 | blk.21.ffn_up.weight      |       0x94e89980 |        0x1810000 |
+|  202 | blk.22.attn_k.weight      |       0x96699980 |         0x1b8000 |
+|  203 | blk.22.attn_norm.weight   |       0x96851980 |           0x4000 |
+|  204 | blk.22.attn_output.weight |       0x96855980 |         0x900000 |
+|  205 | blk.22.attn_q.weight      |       0x97155980 |         0x6e0000 |
+|  206 | blk.22.attn_v.weight      |       0x97835980 |         0x240000 |
+|  207 | blk.22.ffn_down.weight    |       0x97a75980 |        0x1f80000 |
+|  208 | blk.22.ffn_gate.weight    |       0x999f5980 |        0x1810000 |
+|  209 | blk.22.ffn_norm.weight    |       0x9b205980 |           0x4000 |
+|  210 | blk.22.ffn_up.weight      |       0x9b209980 |        0x1810000 |
+|  211 | blk.23.attn_k.weight      |       0x9ca19980 |         0x1b8000 |
+|  212 | blk.23.attn_norm.weight   |       0x9cbd1980 |           0x4000 |
+|  213 | blk.23.attn_output.weight |       0x9cbd5980 |         0x900000 |
+|  214 | blk.23.attn_q.weight      |       0x9d4d5980 |         0x6e0000 |
+|  215 | blk.23.attn_v.weight      |       0x9dbb5980 |         0x240000 |
+|  216 | blk.23.ffn_down.weight    |       0x9ddf5980 |        0x1f80000 |
+|  217 | blk.23.ffn_gate.weight    |       0x9fd75980 |        0x1810000 |
+|  218 | blk.23.ffn_norm.weight    |       0xa1585980 |           0x4000 |
+|  219 | blk.23.ffn_up.weight      |       0xa1589980 |        0x1810000 |
+|  220 | blk.24.attn_k.weight      |       0xa2d99980 |         0x1b8000 |
+|  221 | blk.24.attn_norm.weight   |       0xa2f51980 |           0x4000 |
+|  222 | blk.24.attn_output.weight |       0xa2f55980 |         0x900000 |
+|  223 | blk.24.attn_q.weight      |       0xa3855980 |         0x6e0000 |
+|  224 | blk.24.attn_v.weight      |       0xa3f35980 |         0x240000 |
+|  225 | blk.24.ffn_down.weight    |       0xa4175980 |        0x1f80000 |
+|  226 | blk.24.ffn_gate.weight    |       0xa60f5980 |        0x1810000 |
+|  227 | blk.24.ffn_norm.weight    |       0xa7905980 |           0x4000 |
+|  228 | blk.24.ffn_up.weight      |       0xa7909980 |        0x1810000 |
+|  229 | blk.25.attn_k.weight      |       0xa9119980 |         0x1b8000 |
+|  230 | blk.25.attn_norm.weight   |       0xa92d1980 |           0x4000 |
+|  231 | blk.25.attn_output.weight |       0xa92d5980 |         0x900000 |
+|  232 | blk.25.attn_q.weight      |       0xa9bd5980 |         0x6e0000 |
+|  233 | blk.25.attn_v.weight      |       0xaa2b5980 |         0x240000 |
+|  234 | blk.25.ffn_down.weight    |       0xaa4f5980 |        0x1f80000 |
+|  235 | blk.25.ffn_gate.weight    |       0xac475980 |        0x1810000 |
+|  236 | blk.25.ffn_norm.weight    |       0xadc85980 |           0x4000 |
+|  237 | blk.25.ffn_up.weight      |       0xadc89980 |        0x1810000 |
+|  238 | blk.26.attn_k.weight      |       0xaf499980 |         0x1b8000 |
+|  239 | blk.26.attn_norm.weight   |       0xaf651980 |           0x4000 |
+|  240 | blk.26.attn_output.weight |       0xaf655980 |         0x900000 |
+|  241 | blk.26.attn_q.weight      |       0xaff55980 |         0x6e0000 |
+|  242 | blk.26.attn_v.weight      |       0xb0635980 |         0x240000 |
+|  243 | blk.26.ffn_down.weight    |       0xb0875980 |        0x1f80000 |
+|  244 | blk.26.ffn_gate.weight    |       0xb27f5980 |        0x1810000 |
+|  245 | blk.26.ffn_norm.weight    |       0xb4005980 |           0x4000 |
+|  246 | blk.26.ffn_up.weight      |       0xb4009980 |        0x1810000 |
+|  247 | blk.27.attn_k.weight      |       0xb5819980 |         0x1b8000 |
+|  248 | blk.27.attn_norm.weight   |       0xb59d1980 |           0x4000 |
+|  249 | blk.27.attn_output.weight |       0xb59d5980 |         0x900000 |
+|  250 | blk.27.attn_q.weight      |       0xb62d5980 |         0x6e0000 |
+|  251 | blk.27.attn_v.weight      |       0xb69b5980 |         0x240000 |
+|  252 | blk.27.ffn_down.weight    |       0xb6bf5980 |        0x1f80000 |
+|  253 | blk.27.ffn_gate.weight    |       0xb8b75980 |        0x1810000 |
+|  254 | blk.27.ffn_norm.weight    |       0xba385980 |           0x4000 |
+|  255 | blk.27.ffn_up.weight      |       0xba389980 |        0x1810000 |
+|  256 | blk.28.attn_k.weight      |       0xbbb99980 |         0x1b8000 |
+|  257 | blk.28.attn_norm.weight   |       0xbbd51980 |           0x4000 |
+|  258 | blk.28.attn_output.weight |       0xbbd55980 |         0x900000 |
+|  259 | blk.28.attn_q.weight      |       0xbc655980 |         0x6e0000 |
+|  260 | blk.28.attn_v.weight      |       0xbcd35980 |         0x240000 |
+|  261 | blk.28.ffn_down.weight    |       0xbcf75980 |        0x1f80000 |
+|  262 | blk.28.ffn_gate.weight    |       0xbeef5980 |        0x1810000 |
+|  263 | blk.28.ffn_norm.weight    |       0xc0705980 |           0x4000 |
+|  264 | blk.28.ffn_up.weight      |       0xc0709980 |        0x1810000 |
+|  265 | blk.29.attn_k.weight      |       0xc1f19980 |         0x1b8000 |
+|  266 | blk.29.attn_norm.weight   |       0xc20d1980 |           0x4000 |
+|  267 | blk.29.attn_output.weight |       0xc20d5980 |         0x900000 |
+|  268 | blk.29.attn_q.weight      |       0xc29d5980 |         0x6e0000 |
+|  269 | blk.29.attn_v.weight      |       0xc30b5980 |         0x240000 |
+|  270 | blk.29.ffn_down.weight    |       0xc32f5980 |        0x1f80000 |
+|  271 | blk.29.ffn_gate.weight    |       0xc5275980 |        0x1810000 |
+|  272 | blk.29.ffn_norm.weight    |       0xc6a85980 |           0x4000 |
+|  273 | blk.29.ffn_up.weight      |       0xc6a89980 |        0x1810000 |
+|  274 | blk.30.attn_k.weight      |       0xc8299980 |         0x1b8000 |
+|  275 | blk.30.attn_norm.weight   |       0xc8451980 |           0x4000 |
+|  276 | blk.30.attn_output.weight |       0xc8455980 |         0x900000 |
+|  277 | blk.30.attn_q.weight      |       0xc8d55980 |         0x6e0000 |
+|  278 | blk.30.attn_v.weight      |       0xc9435980 |         0x240000 |
+|  279 | blk.30.ffn_down.weight    |       0xc9675980 |        0x1f80000 |
+|  280 | blk.30.ffn_gate.weight    |       0xcb5f5980 |        0x1810000 |
+|  281 | blk.30.ffn_norm.weight    |       0xcce05980 |           0x4000 |
+|  282 | blk.30.ffn_up.weight      |       0xcce09980 |        0x1810000 |
+|  283 | blk.31.attn_k.weight      |       0xce619980 |         0x150000 |
+|  284 | blk.31.attn_norm.weight   |       0xce769980 |           0x4000 |
+|  285 | blk.31.attn_output.weight |       0xce76d980 |         0x900000 |
+|  286 | blk.31.attn_q.weight      |       0xcf06d980 |         0x540000 |
+|  287 | blk.31.attn_v.weight      |       0xcf5ad980 |         0x1b8000 |
+|  288 | blk.31.ffn_down.weight    |       0xcf765980 |        0x1f80000 |
+|  289 | blk.31.ffn_gate.weight    |       0xd16e5980 |        0x1810000 |
+|  290 | blk.31.ffn_norm.weight    |       0xd2ef5980 |           0x4000 |
+|  291 | blk.31.ffn_up.weight      |       0xd2ef9980 |        0x1810000 |
+### <a name="base">Base Tensor Group : ~1B Elements</a>
+| T_ID | Tensor Layer Name  | Human Friendly Tensor Layer Name | Elements          | Shape                 | Type |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
+|    0 | output.weight      | Output (W)                       | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q3_K |
+|    1 | output_norm.weight | Output Normalization (W)         | (  ~4K)      4096 | 4096 x      1 x 1 x 1 | F32  |
+|    2 | rope_freqs.weight  | Rope_Freqs (W)                   | (   64)        64 |   64 x      1 x 1 x 1 | F32  |
+|    3 | token_embd.weight  | Token Embedding (W)              | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q3_K |
+- Total elements in base: ( ~1B) 1050677312
+- Percentage of total elements: 13.08%
+### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|    4 | blk.0.attn_k.weight      | Block 0 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|    5 | blk.0.attn_norm.weight   | Block 0 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|    6 | blk.0.attn_output.weight | Block 0 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|    7 | blk.0.attn_q.weight      | Block 0 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|    8 | blk.0.attn_v.weight      | Block 0 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|    9 | blk.0.ffn_down.weight    | Block 0 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   10 | blk.0.ffn_gate.weight    | Block 0 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   11 | blk.0.ffn_norm.weight    | Block 0 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   12 | blk.0.ffn_up.weight      | Block 0 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.0: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   13 | blk.1.attn_k.weight      | Block 1 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   14 | blk.1.attn_norm.weight   | Block 1 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   15 | blk.1.attn_output.weight | Block 1 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   16 | blk.1.attn_q.weight      | Block 1 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   17 | blk.1.attn_v.weight      | Block 1 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   18 | blk.1.ffn_down.weight    | Block 1 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   19 | blk.1.ffn_gate.weight    | Block 1 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   20 | blk.1.ffn_norm.weight    | Block 1 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   21 | blk.1.ffn_up.weight      | Block 1 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.1: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   22 | blk.2.attn_k.weight      | Block 2 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   23 | blk.2.attn_norm.weight   | Block 2 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   24 | blk.2.attn_output.weight | Block 2 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   25 | blk.2.attn_q.weight      | Block 2 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   26 | blk.2.attn_v.weight      | Block 2 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   27 | blk.2.ffn_down.weight    | Block 2 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   28 | blk.2.ffn_gate.weight    | Block 2 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   29 | blk.2.ffn_norm.weight    | Block 2 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   30 | blk.2.ffn_up.weight      | Block 2 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.2: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   31 | blk.3.attn_k.weight      | Block 3 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   32 | blk.3.attn_norm.weight   | Block 3 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   33 | blk.3.attn_output.weight | Block 3 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   34 | blk.3.attn_q.weight      | Block 3 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   35 | blk.3.attn_v.weight      | Block 3 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   36 | blk.3.ffn_down.weight    | Block 3 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   37 | blk.3.ffn_gate.weight    | Block 3 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   38 | blk.3.ffn_norm.weight    | Block 3 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   39 | blk.3.ffn_up.weight      | Block 3 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.3: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   40 | blk.4.attn_k.weight      | Block 4 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   41 | blk.4.attn_norm.weight   | Block 4 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   42 | blk.4.attn_output.weight | Block 4 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   43 | blk.4.attn_q.weight      | Block 4 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   44 | blk.4.attn_v.weight      | Block 4 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   45 | blk.4.ffn_down.weight    | Block 4 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   46 | blk.4.ffn_gate.weight    | Block 4 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   47 | blk.4.ffn_norm.weight    | Block 4 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   48 | blk.4.ffn_up.weight      | Block 4 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.4: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   49 | blk.5.attn_k.weight      | Block 5 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   50 | blk.5.attn_norm.weight   | Block 5 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   51 | blk.5.attn_output.weight | Block 5 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   52 | blk.5.attn_q.weight      | Block 5 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   53 | blk.5.attn_v.weight      | Block 5 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   54 | blk.5.ffn_down.weight    | Block 5 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   55 | blk.5.ffn_gate.weight    | Block 5 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   56 | blk.5.ffn_norm.weight    | Block 5 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   57 | blk.5.ffn_up.weight      | Block 5 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.5: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   58 | blk.6.attn_k.weight      | Block 6 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   59 | blk.6.attn_norm.weight   | Block 6 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   60 | blk.6.attn_output.weight | Block 6 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   61 | blk.6.attn_q.weight      | Block 6 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   62 | blk.6.attn_v.weight      | Block 6 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   63 | blk.6.ffn_down.weight    | Block 6 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   64 | blk.6.ffn_gate.weight    | Block 6 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   65 | blk.6.ffn_norm.weight    | Block 6 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   66 | blk.6.ffn_up.weight      | Block 6 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.6: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   67 | blk.7.attn_k.weight      | Block 7 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   68 | blk.7.attn_norm.weight   | Block 7 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   69 | blk.7.attn_output.weight | Block 7 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   70 | blk.7.attn_q.weight      | Block 7 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   71 | blk.7.attn_v.weight      | Block 7 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   72 | blk.7.ffn_down.weight    | Block 7 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   73 | blk.7.ffn_gate.weight    | Block 7 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   74 | blk.7.ffn_norm.weight    | Block 7 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   75 | blk.7.ffn_up.weight      | Block 7 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.7: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   76 | blk.8.attn_k.weight      | Block 8 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   77 | blk.8.attn_norm.weight   | Block 8 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   78 | blk.8.attn_output.weight | Block 8 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   79 | blk.8.attn_q.weight      | Block 8 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   80 | blk.8.attn_v.weight      | Block 8 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   81 | blk.8.ffn_down.weight    | Block 8 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   82 | blk.8.ffn_gate.weight    | Block 8 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   83 | blk.8.ffn_norm.weight    | Block 8 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   84 | blk.8.ffn_up.weight      | Block 8 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.8: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   85 | blk.9.attn_k.weight      | Block 9 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   86 | blk.9.attn_norm.weight   | Block 9 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   87 | blk.9.attn_output.weight | Block 9 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   88 | blk.9.attn_q.weight      | Block 9 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   89 | blk.9.attn_v.weight      | Block 9 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   90 | blk.9.ffn_down.weight    | Block 9 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   91 | blk.9.ffn_gate.weight    | Block 9 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   92 | blk.9.ffn_norm.weight    | Block 9 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   93 | blk.9.ffn_up.weight      | Block 9 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.9: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|   94 | blk.10.attn_k.weight      | Block 10 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   95 | blk.10.attn_norm.weight   | Block 10 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   96 | blk.10.attn_output.weight | Block 10 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   97 | blk.10.attn_q.weight      | Block 10 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   98 | blk.10.attn_v.weight      | Block 10 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   99 | blk.10.ffn_down.weight    | Block 10 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  100 | blk.10.ffn_gate.weight    | Block 10 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  101 | blk.10.ffn_norm.weight    | Block 10 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  102 | blk.10.ffn_up.weight      | Block 10 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.10: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  103 | blk.11.attn_k.weight      | Block 11 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  104 | blk.11.attn_norm.weight   | Block 11 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  105 | blk.11.attn_output.weight | Block 11 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  106 | blk.11.attn_q.weight      | Block 11 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  107 | blk.11.attn_v.weight      | Block 11 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  108 | blk.11.ffn_down.weight    | Block 11 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  109 | blk.11.ffn_gate.weight    | Block 11 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  110 | blk.11.ffn_norm.weight    | Block 11 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  111 | blk.11.ffn_up.weight      | Block 11 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.11: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  112 | blk.12.attn_k.weight      | Block 12 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  113 | blk.12.attn_norm.weight   | Block 12 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  114 | blk.12.attn_output.weight | Block 12 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  115 | blk.12.attn_q.weight      | Block 12 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  116 | blk.12.attn_v.weight      | Block 12 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  117 | blk.12.ffn_down.weight    | Block 12 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  118 | blk.12.ffn_gate.weight    | Block 12 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  119 | blk.12.ffn_norm.weight    | Block 12 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  120 | blk.12.ffn_up.weight      | Block 12 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.12: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  121 | blk.13.attn_k.weight      | Block 13 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  122 | blk.13.attn_norm.weight   | Block 13 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  123 | blk.13.attn_output.weight | Block 13 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  124 | blk.13.attn_q.weight      | Block 13 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  125 | blk.13.attn_v.weight      | Block 13 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  126 | blk.13.ffn_down.weight    | Block 13 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  127 | blk.13.ffn_gate.weight    | Block 13 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  128 | blk.13.ffn_norm.weight    | Block 13 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  129 | blk.13.ffn_up.weight      | Block 13 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.13: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  130 | blk.14.attn_k.weight      | Block 14 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  131 | blk.14.attn_norm.weight   | Block 14 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  132 | blk.14.attn_output.weight | Block 14 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  133 | blk.14.attn_q.weight      | Block 14 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  134 | blk.14.attn_v.weight      | Block 14 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  135 | blk.14.ffn_down.weight    | Block 14 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  136 | blk.14.ffn_gate.weight    | Block 14 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  137 | blk.14.ffn_norm.weight    | Block 14 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  138 | blk.14.ffn_up.weight      | Block 14 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.14: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  139 | blk.15.attn_k.weight      | Block 15 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  140 | blk.15.attn_norm.weight   | Block 15 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  141 | blk.15.attn_output.weight | Block 15 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  142 | blk.15.attn_q.weight      | Block 15 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  143 | blk.15.attn_v.weight      | Block 15 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  144 | blk.15.ffn_down.weight    | Block 15 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  145 | blk.15.ffn_gate.weight    | Block 15 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  146 | blk.15.ffn_norm.weight    | Block 15 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  147 | blk.15.ffn_up.weight      | Block 15 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.15: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  148 | blk.16.attn_k.weight      | Block 16 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  149 | blk.16.attn_norm.weight   | Block 16 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  150 | blk.16.attn_output.weight | Block 16 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  151 | blk.16.attn_q.weight      | Block 16 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  152 | blk.16.attn_v.weight      | Block 16 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  153 | blk.16.ffn_down.weight    | Block 16 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  154 | blk.16.ffn_gate.weight    | Block 16 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  155 | blk.16.ffn_norm.weight    | Block 16 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  156 | blk.16.ffn_up.weight      | Block 16 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.16: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  157 | blk.17.attn_k.weight      | Block 17 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  158 | blk.17.attn_norm.weight   | Block 17 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  159 | blk.17.attn_output.weight | Block 17 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  160 | blk.17.attn_q.weight      | Block 17 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  161 | blk.17.attn_v.weight      | Block 17 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  162 | blk.17.ffn_down.weight    | Block 17 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  163 | blk.17.ffn_gate.weight    | Block 17 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  164 | blk.17.ffn_norm.weight    | Block 17 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  165 | blk.17.ffn_up.weight      | Block 17 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.17: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  166 | blk.18.attn_k.weight      | Block 18 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  167 | blk.18.attn_norm.weight   | Block 18 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  168 | blk.18.attn_output.weight | Block 18 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  169 | blk.18.attn_q.weight      | Block 18 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  170 | blk.18.attn_v.weight      | Block 18 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  171 | blk.18.ffn_down.weight    | Block 18 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  172 | blk.18.ffn_gate.weight    | Block 18 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  173 | blk.18.ffn_norm.weight    | Block 18 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  174 | blk.18.ffn_up.weight      | Block 18 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.18: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  175 | blk.19.attn_k.weight      | Block 19 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  176 | blk.19.attn_norm.weight   | Block 19 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  177 | blk.19.attn_output.weight | Block 19 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  178 | blk.19.attn_q.weight      | Block 19 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  179 | blk.19.attn_v.weight      | Block 19 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  180 | blk.19.ffn_down.weight    | Block 19 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  181 | blk.19.ffn_gate.weight    | Block 19 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  182 | blk.19.ffn_norm.weight    | Block 19 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  183 | blk.19.ffn_up.weight      | Block 19 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.19: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  184 | blk.20.attn_k.weight      | Block 20 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  185 | blk.20.attn_norm.weight   | Block 20 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  186 | blk.20.attn_output.weight | Block 20 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  187 | blk.20.attn_q.weight      | Block 20 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  188 | blk.20.attn_v.weight      | Block 20 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  189 | blk.20.ffn_down.weight    | Block 20 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  190 | blk.20.ffn_gate.weight    | Block 20 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  191 | blk.20.ffn_norm.weight    | Block 20 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  192 | blk.20.ffn_up.weight      | Block 20 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.20: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  193 | blk.21.attn_k.weight      | Block 21 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  194 | blk.21.attn_norm.weight   | Block 21 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  195 | blk.21.attn_output.weight | Block 21 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  196 | blk.21.attn_q.weight      | Block 21 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  197 | blk.21.attn_v.weight      | Block 21 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  198 | blk.21.ffn_down.weight    | Block 21 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  199 | blk.21.ffn_gate.weight    | Block 21 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  200 | blk.21.ffn_norm.weight    | Block 21 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  201 | blk.21.ffn_up.weight      | Block 21 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.21: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  202 | blk.22.attn_k.weight      | Block 22 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  203 | blk.22.attn_norm.weight   | Block 22 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  204 | blk.22.attn_output.weight | Block 22 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  205 | blk.22.attn_q.weight      | Block 22 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  206 | blk.22.attn_v.weight      | Block 22 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  207 | blk.22.ffn_down.weight    | Block 22 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  208 | blk.22.ffn_gate.weight    | Block 22 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  209 | blk.22.ffn_norm.weight    | Block 22 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  210 | blk.22.ffn_up.weight      | Block 22 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.22: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  211 | blk.23.attn_k.weight      | Block 23 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  212 | blk.23.attn_norm.weight   | Block 23 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  213 | blk.23.attn_output.weight | Block 23 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  214 | blk.23.attn_q.weight      | Block 23 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  215 | blk.23.attn_v.weight      | Block 23 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  216 | blk.23.ffn_down.weight    | Block 23 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  217 | blk.23.ffn_gate.weight    | Block 23 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  218 | blk.23.ffn_norm.weight    | Block 23 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  219 | blk.23.ffn_up.weight      | Block 23 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.23: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  220 | blk.24.attn_k.weight      | Block 24 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  221 | blk.24.attn_norm.weight   | Block 24 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  222 | blk.24.attn_output.weight | Block 24 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  223 | blk.24.attn_q.weight      | Block 24 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  224 | blk.24.attn_v.weight      | Block 24 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  225 | blk.24.ffn_down.weight    | Block 24 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  226 | blk.24.ffn_gate.weight    | Block 24 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  227 | blk.24.ffn_norm.weight    | Block 24 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  228 | blk.24.ffn_up.weight      | Block 24 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.24: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  229 | blk.25.attn_k.weight      | Block 25 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  230 | blk.25.attn_norm.weight   | Block 25 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  231 | blk.25.attn_output.weight | Block 25 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  232 | blk.25.attn_q.weight      | Block 25 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  233 | blk.25.attn_v.weight      | Block 25 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  234 | blk.25.ffn_down.weight    | Block 25 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  235 | blk.25.ffn_gate.weight    | Block 25 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  236 | blk.25.ffn_norm.weight    | Block 25 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  237 | blk.25.ffn_up.weight      | Block 25 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.25: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  238 | blk.26.attn_k.weight      | Block 26 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  239 | blk.26.attn_norm.weight   | Block 26 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  240 | blk.26.attn_output.weight | Block 26 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  241 | blk.26.attn_q.weight      | Block 26 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  242 | blk.26.attn_v.weight      | Block 26 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  243 | blk.26.ffn_down.weight    | Block 26 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  244 | blk.26.ffn_gate.weight    | Block 26 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  245 | blk.26.ffn_norm.weight    | Block 26 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  246 | blk.26.ffn_up.weight      | Block 26 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.26: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  247 | blk.27.attn_k.weight      | Block 27 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  248 | blk.27.attn_norm.weight   | Block 27 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  249 | blk.27.attn_output.weight | Block 27 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  250 | blk.27.attn_q.weight      | Block 27 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  251 | blk.27.attn_v.weight      | Block 27 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  252 | blk.27.ffn_down.weight    | Block 27 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  253 | blk.27.ffn_gate.weight    | Block 27 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  254 | blk.27.ffn_norm.weight    | Block 27 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  255 | blk.27.ffn_up.weight      | Block 27 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.27: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  256 | blk.28.attn_k.weight      | Block 28 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  257 | blk.28.attn_norm.weight   | Block 28 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  258 | blk.28.attn_output.weight | Block 28 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  259 | blk.28.attn_q.weight      | Block 28 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  260 | blk.28.attn_v.weight      | Block 28 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  261 | blk.28.ffn_down.weight    | Block 28 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  262 | blk.28.ffn_gate.weight    | Block 28 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  263 | blk.28.ffn_norm.weight    | Block 28 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  264 | blk.28.ffn_up.weight      | Block 28 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.28: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  265 | blk.29.attn_k.weight      | Block 29 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  266 | blk.29.attn_norm.weight   | Block 29 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  267 | blk.29.attn_output.weight | Block 29 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  268 | blk.29.attn_q.weight      | Block 29 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  269 | blk.29.attn_v.weight      | Block 29 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  270 | blk.29.ffn_down.weight    | Block 29 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  271 | blk.29.ffn_gate.weight    | Block 29 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  272 | blk.29.ffn_norm.weight    | Block 29 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  273 | blk.29.ffn_up.weight      | Block 29 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.29: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  274 | blk.30.attn_k.weight      | Block 30 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  275 | blk.30.attn_norm.weight   | Block 30 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  276 | blk.30.attn_output.weight | Block 30 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  277 | blk.30.attn_q.weight      | Block 30 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  278 | blk.30.attn_v.weight      | Block 30 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  279 | blk.30.ffn_down.weight    | Block 30 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  280 | blk.30.ffn_gate.weight    | Block 30 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  281 | blk.30.ffn_norm.weight    | Block 30 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  282 | blk.30.ffn_up.weight      | Block 30 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.30: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  283 | blk.31.attn_k.weight      | Block 31 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  284 | blk.31.attn_norm.weight   | Block 31 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  285 | blk.31.attn_output.weight | Block 31 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  286 | blk.31.attn_q.weight      | Block 31 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  287 | blk.31.attn_v.weight      | Block 31 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  288 | blk.31.ffn_down.weight    | Block 31 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  289 | blk.31.ffn_gate.weight    | Block 31 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  290 | blk.31.ffn_norm.weight    | Block 31 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  291 | blk.31.ffn_up.weight      | Block 31 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.31: (~218M) 218112000
+- Percentage of total elements: 2.72%

scores/Llama-Guard-3-8B-Q3_K_S.md ADDED Viewed

	@@ -0,0 +1,978 @@

+# Llama-Guard-3-8B-Q3_K_S.gguf - GGUF Internal File Dump
+- Endian: LITTLE endian
+## Key Value Metadata Store
+There are 39 key-value pairs in this file
+| POS | TYPE     |  Count | Key                                    | Value                                                               |
+|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
+|   1 | UINT32   |      1 | GGUF.version                           | 3                                                                   |
+|   2 | UINT64   |      1 | GGUF.tensor_count                      | 292                                                                 |
+|   3 | UINT64   |      1 | GGUF.kv_count                          | 36                                                                  |
+|   4 | STRING   |      1 | general.architecture                   | `llama`                                                             |
+|   5 | STRING   |      1 | general.type                           | `model`                                                             |
+|   6 | STRING   |      1 | general.name                           | `Llama Guard 3 8B`                                                  |
+|   7 | STRING   |      1 | general.basename                       | `Llama-Guard-3`                                                     |
+|   8 | STRING   |      1 | general.size_label                     | `8B`                                                                |
+|   9 | STRING   |      1 | general.license                        | `llama3.1`                                                          |
+|  10 | UINT32   |      1 | general.base_model.count               | 1                                                                   |
+|  11 | STRING   |      1 | general.base_model.0.name              | `Meta Llama 3.1 8B`                                                 |
+|  12 | STRING   |      1 | general.base_model.0.organization      | `Meta Llama`                                                        |
+|  13 | STRING   |      1 | general.base_model.0.repo_url          | `https://huggingface.co/meta-llama/Meta-Llama-3.1-8B`               |
+|  14 | [STRING] |      6 | general.tags                           | [ `facebook`, `meta`, `pytorch`, `llama`, `llama-3`, ... ]          |
+|  15 | [STRING] |      1 | general.languages                      | [ `en` ]                                                            |
+|  16 | UINT32   |      1 | llama.block_count                      | 32                                                                  |
+|  17 | UINT32   |      1 | llama.context_length                   | 131072                                                              |
+|  18 | UINT32   |      1 | llama.embedding_length                 | 4096                                                                |
+|  19 | UINT32   |      1 | llama.feed_forward_length              | 14336                                                               |
+|  20 | UINT32   |      1 | llama.attention.head_count             | 32                                                                  |
+|  21 | UINT32   |      1 | llama.attention.head_count_kv          | 8                                                                   |
+|  22 | FLOAT32  |      1 | llama.rope.freq_base                   | 500000.0                                                            |
+|  23 | FLOAT32  |      1 | llama.attention.layer_norm_rms_epsilon | 1e-05                                                               |
+|  24 | UINT32   |      1 | llama.vocab_size                       | 128256                                                              |
+|  25 | UINT32   |      1 | llama.rope.dimension_count             | 128                                                                 |
+|  26 | STRING   |      1 | tokenizer.ggml.model                   | `gpt2`                                                              |
+|  27 | STRING   |      1 | tokenizer.ggml.pre                     | `smaug-bpe`                                                         |
+|  28 | [STRING] | 128256 | tokenizer.ggml.tokens                  | [ `!`, `"`, `#`, `$`, `%`, ... ]                                    |
+|  29 | [INT32]  | 128256 | tokenizer.ggml.token_type              | [ 1, 1, 1, 1, 1, 1, 1, ... ]                                        |
+|  30 | [STRING] | 280147 | tokenizer.ggml.merges                  | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]                    |
+|  31 | UINT32   |      1 | tokenizer.ggml.bos_token_id            | 128000                                                              |
+|  32 | UINT32   |      1 | tokenizer.ggml.eos_token_id            | 128009                                                              |
+|  33 | STRING   |      1 | tokenizer.chat_template                | `{% if messages|length % 2 == 0`...`assistant<|end_header_id|>" }}` |
+|  34 | UINT32   |      1 | general.quantization_version           | 2                                                                   |
+|  35 | UINT32   |      1 | general.file_type                      | 11                                                                  |
+|  36 | STRING   |      1 | quantize.imatrix.file                  | `./imatrix/imatrix-Llama-Guard-3-8B-small.dat`                      |
+|  37 | STRING   |      1 | quantize.imatrix.dataset               | `../../datasets/imatrix/calibration_eur_small.txt`                  |
+|  38 | INT32    |      1 | quantize.imatrix.entries_count         | 224                                                                 |
+|  39 | INT32    |      1 | quantize.imatrix.chunks_count          | 962                                                                 |
+## Tensors Overview ~8B Elements
+Total number of elements in all tensors: 8030261312 Elements
+- [Llama-Guard-3-8B-Q3\_K\_S.gguf - GGUF Internal File Dump](#llama-guard-3-8b-q3_k_sgguf---gguf-internal-file-dump)
+  - [Key Value Metadata Store](#key-value-metadata-store)
+  - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
+    - [Tensor Data Offset](#tensor-data-offset)
+    - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
+    - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
+    - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
+    - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
+    - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
+    - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
+    - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
+    - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
+    - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
+    - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
+    - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
+    - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
+    - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
+    - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
+    - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
+    - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
+    - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
+    - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
+    - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
+    - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
+    - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
+    - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
+    - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
+    - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
+    - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
+    - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
+    - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
+    - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
+    - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
+    - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
+    - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
+    - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
+    - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
+### Tensor Data Offset
+This table contains the offset and data segment relative to start of file
+| T_ID | Tensor Layer Name         |  Data Offset (B) |    Data Size (B) |
+|-----:|:--------------------------|-----------------:|-----------------:|
+|    0 | output.weight             |         0x779880 |        0xd746000 |
+|    1 | output_norm.weight        |        0xdebf880 |           0x4000 |
+|    2 | rope_freqs.weight         |        0xdec3880 |            0x100 |
+|    3 | token_embd.weight         |        0xdec3980 |        0xa464000 |
+|    4 | blk.0.attn_k.weight       |       0x18327980 |         0x150000 |
+|    5 | blk.0.attn_norm.weight    |       0x18477980 |           0x4000 |
+|    6 | blk.0.attn_output.weight  |       0x1847b980 |         0x6e0000 |
+|    7 | blk.0.attn_q.weight       |       0x18b5b980 |         0x540000 |
+|    8 | blk.0.attn_v.weight       |       0x1909b980 |         0x1b8000 |
+|    9 | blk.0.ffn_down.weight     |       0x19253980 |        0x1810000 |
+|   10 | blk.0.ffn_gate.weight     |       0x1aa63980 |        0x1260000 |
+|   11 | blk.0.ffn_norm.weight     |       0x1bcc3980 |           0x4000 |
+|   12 | blk.0.ffn_up.weight       |       0x1bcc7980 |        0x1260000 |
+|   13 | blk.1.attn_k.weight       |       0x1cf27980 |         0x150000 |
+|   14 | blk.1.attn_norm.weight    |       0x1d077980 |           0x4000 |
+|   15 | blk.1.attn_output.weight  |       0x1d07b980 |         0x6e0000 |
+|   16 | blk.1.attn_q.weight       |       0x1d75b980 |         0x540000 |
+|   17 | blk.1.attn_v.weight       |       0x1dc9b980 |         0x1b8000 |
+|   18 | blk.1.ffn_down.weight     |       0x1de53980 |        0x1f80000 |
+|   19 | blk.1.ffn_gate.weight     |       0x1fdd3980 |        0x1260000 |
+|   20 | blk.1.ffn_norm.weight     |       0x21033980 |           0x4000 |
+|   21 | blk.1.ffn_up.weight       |       0x21037980 |        0x1260000 |
+|   22 | blk.2.attn_k.weight       |       0x22297980 |         0x150000 |
+|   23 | blk.2.attn_norm.weight    |       0x223e7980 |           0x4000 |
+|   24 | blk.2.attn_output.weight  |       0x223eb980 |         0x6e0000 |
+|   25 | blk.2.attn_q.weight       |       0x22acb980 |         0x540000 |
+|   26 | blk.2.attn_v.weight       |       0x2300b980 |         0x1b8000 |
+|   27 | blk.2.ffn_down.weight     |       0x231c3980 |        0x1810000 |
+|   28 | blk.2.ffn_gate.weight     |       0x249d3980 |        0x1260000 |
+|   29 | blk.2.ffn_norm.weight     |       0x25c33980 |           0x4000 |
+|   30 | blk.2.ffn_up.weight       |       0x25c37980 |        0x1260000 |
+|   31 | blk.3.attn_k.weight       |       0x26e97980 |         0x150000 |
+|   32 | blk.3.attn_norm.weight    |       0x26fe7980 |           0x4000 |
+|   33 | blk.3.attn_output.weight  |       0x26feb980 |         0x6e0000 |
+|   34 | blk.3.attn_q.weight       |       0x276cb980 |         0x540000 |
+|   35 | blk.3.attn_v.weight       |       0x27c0b980 |         0x1b8000 |
+|   36 | blk.3.ffn_down.weight     |       0x27dc3980 |        0x1810000 |
+|   37 | blk.3.ffn_gate.weight     |       0x295d3980 |        0x1260000 |
+|   38 | blk.3.ffn_norm.weight     |       0x2a833980 |           0x4000 |
+|   39 | blk.3.ffn_up.weight       |       0x2a837980 |        0x1260000 |
+|   40 | blk.4.attn_k.weight       |       0x2ba97980 |         0x150000 |
+|   41 | blk.4.attn_norm.weight    |       0x2bbe7980 |           0x4000 |
+|   42 | blk.4.attn_output.weight  |       0x2bbeb980 |         0x6e0000 |
+|   43 | blk.4.attn_q.weight       |       0x2c2cb980 |         0x540000 |
+|   44 | blk.4.attn_v.weight       |       0x2c80b980 |         0x1b8000 |
+|   45 | blk.4.ffn_down.weight     |       0x2c9c3980 |        0x1810000 |
+|   46 | blk.4.ffn_gate.weight     |       0x2e1d3980 |        0x1260000 |
+|   47 | blk.4.ffn_norm.weight     |       0x2f433980 |           0x4000 |
+|   48 | blk.4.ffn_up.weight       |       0x2f437980 |        0x1260000 |
+|   49 | blk.5.attn_k.weight       |       0x30697980 |         0x150000 |
+|   50 | blk.5.attn_norm.weight    |       0x307e7980 |           0x4000 |
+|   51 | blk.5.attn_output.weight  |       0x307eb980 |         0x6e0000 |
+|   52 | blk.5.attn_q.weight       |       0x30ecb980 |         0x540000 |
+|   53 | blk.5.attn_v.weight       |       0x3140b980 |         0x1b8000 |
+|   54 | blk.5.ffn_down.weight     |       0x315c3980 |        0x1810000 |
+|   55 | blk.5.ffn_gate.weight     |       0x32dd3980 |        0x1260000 |
+|   56 | blk.5.ffn_norm.weight     |       0x34033980 |           0x4000 |
+|   57 | blk.5.ffn_up.weight       |       0x34037980 |        0x1260000 |
+|   58 | blk.6.attn_k.weight       |       0x35297980 |         0x150000 |
+|   59 | blk.6.attn_norm.weight    |       0x353e7980 |           0x4000 |
+|   60 | blk.6.attn_output.weight  |       0x353eb980 |         0x6e0000 |
+|   61 | blk.6.attn_q.weight       |       0x35acb980 |         0x540000 |
+|   62 | blk.6.attn_v.weight       |       0x3600b980 |         0x1b8000 |
+|   63 | blk.6.ffn_down.weight     |       0x361c3980 |        0x1810000 |
+|   64 | blk.6.ffn_gate.weight     |       0x379d3980 |        0x1260000 |
+|   65 | blk.6.ffn_norm.weight     |       0x38c33980 |           0x4000 |
+|   66 | blk.6.ffn_up.weight       |       0x38c37980 |        0x1260000 |
+|   67 | blk.7.attn_k.weight       |       0x39e97980 |         0x150000 |
+|   68 | blk.7.attn_norm.weight    |       0x39fe7980 |           0x4000 |
+|   69 | blk.7.attn_output.weight  |       0x39feb980 |         0x6e0000 |
+|   70 | blk.7.attn_q.weight       |       0x3a6cb980 |         0x540000 |
+|   71 | blk.7.attn_v.weight       |       0x3ac0b980 |         0x1b8000 |
+|   72 | blk.7.ffn_down.weight     |       0x3adc3980 |        0x1810000 |
+|   73 | blk.7.ffn_gate.weight     |       0x3c5d3980 |        0x1260000 |
+|   74 | blk.7.ffn_norm.weight     |       0x3d833980 |           0x4000 |
+|   75 | blk.7.ffn_up.weight       |       0x3d837980 |        0x1260000 |
+|   76 | blk.8.attn_k.weight       |       0x3ea97980 |         0x150000 |
+|   77 | blk.8.attn_norm.weight    |       0x3ebe7980 |           0x4000 |
+|   78 | blk.8.attn_output.weight  |       0x3ebeb980 |         0x6e0000 |
+|   79 | blk.8.attn_q.weight       |       0x3f2cb980 |         0x540000 |
+|   80 | blk.8.attn_v.weight       |       0x3f80b980 |         0x1b8000 |
+|   81 | blk.8.ffn_down.weight     |       0x3f9c3980 |        0x1810000 |
+|   82 | blk.8.ffn_gate.weight     |       0x411d3980 |        0x1260000 |
+|   83 | blk.8.ffn_norm.weight     |       0x42433980 |           0x4000 |
+|   84 | blk.8.ffn_up.weight       |       0x42437980 |        0x1260000 |
+|   85 | blk.9.attn_k.weight       |       0x43697980 |         0x150000 |
+|   86 | blk.9.attn_norm.weight    |       0x437e7980 |           0x4000 |
+|   87 | blk.9.attn_output.weight  |       0x437eb980 |         0x6e0000 |
+|   88 | blk.9.attn_q.weight       |       0x43ecb980 |         0x540000 |
+|   89 | blk.9.attn_v.weight       |       0x4440b980 |         0x1b8000 |
+|   90 | blk.9.ffn_down.weight     |       0x445c3980 |        0x1810000 |
+|   91 | blk.9.ffn_gate.weight     |       0x45dd3980 |        0x1260000 |
+|   92 | blk.9.ffn_norm.weight     |       0x47033980 |           0x4000 |
+|   93 | blk.9.ffn_up.weight       |       0x47037980 |        0x1260000 |
+|   94 | blk.10.attn_k.weight      |       0x48297980 |         0x150000 |
+|   95 | blk.10.attn_norm.weight   |       0x483e7980 |           0x4000 |
+|   96 | blk.10.attn_output.weight |       0x483eb980 |         0x6e0000 |
+|   97 | blk.10.attn_q.weight      |       0x48acb980 |         0x540000 |
+|   98 | blk.10.attn_v.weight      |       0x4900b980 |         0x1b8000 |
+|   99 | blk.10.ffn_down.weight    |       0x491c3980 |        0x1810000 |
+|  100 | blk.10.ffn_gate.weight    |       0x4a9d3980 |        0x1260000 |
+|  101 | blk.10.ffn_norm.weight    |       0x4bc33980 |           0x4000 |
+|  102 | blk.10.ffn_up.weight      |       0x4bc37980 |        0x1260000 |
+|  103 | blk.11.attn_k.weight      |       0x4ce97980 |         0x150000 |
+|  104 | blk.11.attn_norm.weight   |       0x4cfe7980 |           0x4000 |
+|  105 | blk.11.attn_output.weight |       0x4cfeb980 |         0x6e0000 |
+|  106 | blk.11.attn_q.weight      |       0x4d6cb980 |         0x540000 |
+|  107 | blk.11.attn_v.weight      |       0x4dc0b980 |         0x1b8000 |
+|  108 | blk.11.ffn_down.weight    |       0x4ddc3980 |        0x1810000 |
+|  109 | blk.11.ffn_gate.weight    |       0x4f5d3980 |        0x1260000 |
+|  110 | blk.11.ffn_norm.weight    |       0x50833980 |           0x4000 |
+|  111 | blk.11.ffn_up.weight      |       0x50837980 |        0x1260000 |
+|  112 | blk.12.attn_k.weight      |       0x51a97980 |         0x150000 |
+|  113 | blk.12.attn_norm.weight   |       0x51be7980 |           0x4000 |
+|  114 | blk.12.attn_output.weight |       0x51beb980 |         0x6e0000 |
+|  115 | blk.12.attn_q.weight      |       0x522cb980 |         0x540000 |
+|  116 | blk.12.attn_v.weight      |       0x5280b980 |         0x1b8000 |
+|  117 | blk.12.ffn_down.weight    |       0x529c3980 |        0x1810000 |
+|  118 | blk.12.ffn_gate.weight    |       0x541d3980 |        0x1260000 |
+|  119 | blk.12.ffn_norm.weight    |       0x55433980 |           0x4000 |
+|  120 | blk.12.ffn_up.weight      |       0x55437980 |        0x1260000 |
+|  121 | blk.13.attn_k.weight      |       0x56697980 |         0x1b8000 |
+|  122 | blk.13.attn_norm.weight   |       0x5684f980 |           0x4000 |
+|  123 | blk.13.attn_output.weight |       0x56853980 |         0x6e0000 |
+|  124 | blk.13.attn_q.weight      |       0x56f33980 |         0x6e0000 |
+|  125 | blk.13.attn_v.weight      |       0x57613980 |         0x1b8000 |
+|  126 | blk.13.ffn_down.weight    |       0x577cb980 |        0x1810000 |
+|  127 | blk.13.ffn_gate.weight    |       0x58fdb980 |        0x1260000 |
+|  128 | blk.13.ffn_norm.weight    |       0x5a23b980 |           0x4000 |
+|  129 | blk.13.ffn_up.weight      |       0x5a23f980 |        0x1260000 |
+|  130 | blk.14.attn_k.weight      |       0x5b49f980 |         0x1b8000 |
+|  131 | blk.14.attn_norm.weight   |       0x5b657980 |           0x4000 |
+|  132 | blk.14.attn_output.weight |       0x5b65b980 |         0x6e0000 |
+|  133 | blk.14.attn_q.weight      |       0x5bd3b980 |         0x6e0000 |
+|  134 | blk.14.attn_v.weight      |       0x5c41b980 |         0x1b8000 |
+|  135 | blk.14.ffn_down.weight    |       0x5c5d3980 |        0x1810000 |
+|  136 | blk.14.ffn_gate.weight    |       0x5dde3980 |        0x1260000 |
+|  137 | blk.14.ffn_norm.weight    |       0x5f043980 |           0x4000 |
+|  138 | blk.14.ffn_up.weight      |       0x5f047980 |        0x1260000 |
+|  139 | blk.15.attn_k.weight      |       0x602a7980 |         0x150000 |
+|  140 | blk.15.attn_norm.weight   |       0x603f7980 |           0x4000 |
+|  141 | blk.15.attn_output.weight |       0x603fb980 |         0x6e0000 |
+|  142 | blk.15.attn_q.weight      |       0x60adb980 |         0x540000 |
+|  143 | blk.15.attn_v.weight      |       0x6101b980 |         0x1b8000 |
+|  144 | blk.15.ffn_down.weight    |       0x611d3980 |        0x1810000 |
+|  145 | blk.15.ffn_gate.weight    |       0x629e3980 |        0x1260000 |
+|  146 | blk.15.ffn_norm.weight    |       0x63c43980 |           0x4000 |
+|  147 | blk.15.ffn_up.weight      |       0x63c47980 |        0x1260000 |
+|  148 | blk.16.attn_k.weight      |       0x64ea7980 |         0x1b8000 |
+|  149 | blk.16.attn_norm.weight   |       0x6505f980 |           0x4000 |
+|  150 | blk.16.attn_output.weight |       0x65063980 |         0x6e0000 |
+|  151 | blk.16.attn_q.weight      |       0x65743980 |         0x6e0000 |
+|  152 | blk.16.attn_v.weight      |       0x65e23980 |         0x1b8000 |
+|  153 | blk.16.ffn_down.weight    |       0x65fdb980 |        0x1810000 |
+|  154 | blk.16.ffn_gate.weight    |       0x677eb980 |        0x1810000 |
+|  155 | blk.16.ffn_norm.weight    |       0x68ffb980 |           0x4000 |
+|  156 | blk.16.ffn_up.weight      |       0x68fff980 |        0x1810000 |
+|  157 | blk.17.attn_k.weight      |       0x6a80f980 |         0x150000 |
+|  158 | blk.17.attn_norm.weight   |       0x6a95f980 |           0x4000 |
+|  159 | blk.17.attn_output.weight |       0x6a963980 |         0x6e0000 |
+|  160 | blk.17.attn_q.weight      |       0x6b043980 |         0x540000 |
+|  161 | blk.17.attn_v.weight      |       0x6b583980 |         0x1b8000 |
+|  162 | blk.17.ffn_down.weight    |       0x6b73b980 |        0x1f80000 |
+|  163 | blk.17.ffn_gate.weight    |       0x6d6bb980 |        0x1810000 |
+|  164 | blk.17.ffn_norm.weight    |       0x6eecb980 |           0x4000 |
+|  165 | blk.17.ffn_up.weight      |       0x6eecf980 |        0x1810000 |
+|  166 | blk.18.attn_k.weight      |       0x706df980 |         0x1b8000 |
+|  167 | blk.18.attn_norm.weight   |       0x70897980 |           0x4000 |
+|  168 | blk.18.attn_output.weight |       0x7089b980 |         0x6e0000 |
+|  169 | blk.18.attn_q.weight      |       0x70f7b980 |         0x6e0000 |
+|  170 | blk.18.attn_v.weight      |       0x7165b980 |         0x1b8000 |
+|  171 | blk.18.ffn_down.weight    |       0x71813980 |        0x1f80000 |
+|  172 | blk.18.ffn_gate.weight    |       0x73793980 |        0x1810000 |
+|  173 | blk.18.ffn_norm.weight    |       0x74fa3980 |           0x4000 |
+|  174 | blk.18.ffn_up.weight      |       0x74fa7980 |        0x1810000 |
+|  175 | blk.19.attn_k.weight      |       0x767b7980 |         0x1b8000 |
+|  176 | blk.19.attn_norm.weight   |       0x7696f980 |           0x4000 |
+|  177 | blk.19.attn_output.weight |       0x76973980 |         0x6e0000 |
+|  178 | blk.19.attn_q.weight      |       0x77053980 |         0x6e0000 |
+|  179 | blk.19.attn_v.weight      |       0x77733980 |         0x1b8000 |
+|  180 | blk.19.ffn_down.weight    |       0x778eb980 |        0x1f80000 |
+|  181 | blk.19.ffn_gate.weight    |       0x7986b980 |        0x1810000 |
+|  182 | blk.19.ffn_norm.weight    |       0x7b07b980 |           0x4000 |
+|  183 | blk.19.ffn_up.weight      |       0x7b07f980 |        0x1810000 |
+|  184 | blk.20.attn_k.weight      |       0x7c88f980 |         0x1b8000 |
+|  185 | blk.20.attn_norm.weight   |       0x7ca47980 |           0x4000 |
+|  186 | blk.20.attn_output.weight |       0x7ca4b980 |         0x6e0000 |
+|  187 | blk.20.attn_q.weight      |       0x7d12b980 |         0x6e0000 |
+|  188 | blk.20.attn_v.weight      |       0x7d80b980 |         0x1b8000 |
+|  189 | blk.20.ffn_down.weight    |       0x7d9c3980 |        0x1f80000 |
+|  190 | blk.20.ffn_gate.weight    |       0x7f943980 |        0x1810000 |
+|  191 | blk.20.ffn_norm.weight    |       0x81153980 |           0x4000 |
+|  192 | blk.20.ffn_up.weight      |       0x81157980 |        0x1810000 |
+|  193 | blk.21.attn_k.weight      |       0x82967980 |         0x1b8000 |
+|  194 | blk.21.attn_norm.weight   |       0x82b1f980 |           0x4000 |
+|  195 | blk.21.attn_output.weight |       0x82b23980 |         0x6e0000 |
+|  196 | blk.21.attn_q.weight      |       0x83203980 |         0x6e0000 |
+|  197 | blk.21.attn_v.weight      |       0x838e3980 |         0x1b8000 |
+|  198 | blk.21.ffn_down.weight    |       0x83a9b980 |        0x1f80000 |
+|  199 | blk.21.ffn_gate.weight    |       0x85a1b980 |        0x1810000 |
+|  200 | blk.21.ffn_norm.weight    |       0x8722b980 |           0x4000 |
+|  201 | blk.21.ffn_up.weight      |       0x8722f980 |        0x1810000 |
+|  202 | blk.22.attn_k.weight      |       0x88a3f980 |         0x1b8000 |
+|  203 | blk.22.attn_norm.weight   |       0x88bf7980 |           0x4000 |
+|  204 | blk.22.attn_output.weight |       0x88bfb980 |         0x6e0000 |
+|  205 | blk.22.attn_q.weight      |       0x892db980 |         0x6e0000 |
+|  206 | blk.22.attn_v.weight      |       0x899bb980 |         0x1b8000 |
+|  207 | blk.22.ffn_down.weight    |       0x89b73980 |        0x1f80000 |
+|  208 | blk.22.ffn_gate.weight    |       0x8baf3980 |        0x1810000 |
+|  209 | blk.22.ffn_norm.weight    |       0x8d303980 |           0x4000 |
+|  210 | blk.22.ffn_up.weight      |       0x8d307980 |        0x1810000 |
+|  211 | blk.23.attn_k.weight      |       0x8eb17980 |         0x1b8000 |
+|  212 | blk.23.attn_norm.weight   |       0x8eccf980 |           0x4000 |
+|  213 | blk.23.attn_output.weight |       0x8ecd3980 |         0x6e0000 |
+|  214 | blk.23.attn_q.weight      |       0x8f3b3980 |         0x6e0000 |
+|  215 | blk.23.attn_v.weight      |       0x8fa93980 |         0x1b8000 |
+|  216 | blk.23.ffn_down.weight    |       0x8fc4b980 |        0x1f80000 |
+|  217 | blk.23.ffn_gate.weight    |       0x91bcb980 |        0x1810000 |
+|  218 | blk.23.ffn_norm.weight    |       0x933db980 |           0x4000 |
+|  219 | blk.23.ffn_up.weight      |       0x933df980 |        0x1810000 |
+|  220 | blk.24.attn_k.weight      |       0x94bef980 |         0x1b8000 |
+|  221 | blk.24.attn_norm.weight   |       0x94da7980 |           0x4000 |
+|  222 | blk.24.attn_output.weight |       0x94dab980 |         0x6e0000 |
+|  223 | blk.24.attn_q.weight      |       0x9548b980 |         0x6e0000 |
+|  224 | blk.24.attn_v.weight      |       0x95b6b980 |         0x1b8000 |
+|  225 | blk.24.ffn_down.weight    |       0x95d23980 |        0x1f80000 |
+|  226 | blk.24.ffn_gate.weight    |       0x97ca3980 |        0x1810000 |
+|  227 | blk.24.ffn_norm.weight    |       0x994b3980 |           0x4000 |
+|  228 | blk.24.ffn_up.weight      |       0x994b7980 |        0x1810000 |
+|  229 | blk.25.attn_k.weight      |       0x9acc7980 |         0x1b8000 |
+|  230 | blk.25.attn_norm.weight   |       0x9ae7f980 |           0x4000 |
+|  231 | blk.25.attn_output.weight |       0x9ae83980 |         0x6e0000 |
+|  232 | blk.25.attn_q.weight      |       0x9b563980 |         0x6e0000 |
+|  233 | blk.25.attn_v.weight      |       0x9bc43980 |         0x1b8000 |
+|  234 | blk.25.ffn_down.weight    |       0x9bdfb980 |        0x1f80000 |
+|  235 | blk.25.ffn_gate.weight    |       0x9dd7b980 |        0x1810000 |
+|  236 | blk.25.ffn_norm.weight    |       0x9f58b980 |           0x4000 |
+|  237 | blk.25.ffn_up.weight      |       0x9f58f980 |        0x1810000 |
+|  238 | blk.26.attn_k.weight      |       0xa0d9f980 |         0x1b8000 |
+|  239 | blk.26.attn_norm.weight   |       0xa0f57980 |           0x4000 |
+|  240 | blk.26.attn_output.weight |       0xa0f5b980 |         0x6e0000 |
+|  241 | blk.26.attn_q.weight      |       0xa163b980 |         0x6e0000 |
+|  242 | blk.26.attn_v.weight      |       0xa1d1b980 |         0x1b8000 |
+|  243 | blk.26.ffn_down.weight    |       0xa1ed3980 |        0x1f80000 |
+|  244 | blk.26.ffn_gate.weight    |       0xa3e53980 |        0x1810000 |
+|  245 | blk.26.ffn_norm.weight    |       0xa5663980 |           0x4000 |
+|  246 | blk.26.ffn_up.weight      |       0xa5667980 |        0x1810000 |
+|  247 | blk.27.attn_k.weight      |       0xa6e77980 |         0x1b8000 |
+|  248 | blk.27.attn_norm.weight   |       0xa702f980 |           0x4000 |
+|  249 | blk.27.attn_output.weight |       0xa7033980 |         0x6e0000 |
+|  250 | blk.27.attn_q.weight      |       0xa7713980 |         0x6e0000 |
+|  251 | blk.27.attn_v.weight      |       0xa7df3980 |         0x1b8000 |
+|  252 | blk.27.ffn_down.weight    |       0xa7fab980 |        0x1f80000 |
+|  253 | blk.27.ffn_gate.weight    |       0xa9f2b980 |        0x1810000 |
+|  254 | blk.27.ffn_norm.weight    |       0xab73b980 |           0x4000 |
+|  255 | blk.27.ffn_up.weight      |       0xab73f980 |        0x1810000 |
+|  256 | blk.28.attn_k.weight      |       0xacf4f980 |         0x1b8000 |
+|  257 | blk.28.attn_norm.weight   |       0xad107980 |           0x4000 |
+|  258 | blk.28.attn_output.weight |       0xad10b980 |         0x6e0000 |
+|  259 | blk.28.attn_q.weight      |       0xad7eb980 |         0x6e0000 |
+|  260 | blk.28.attn_v.weight      |       0xadecb980 |         0x1b8000 |
+|  261 | blk.28.ffn_down.weight    |       0xae083980 |        0x1f80000 |
+|  262 | blk.28.ffn_gate.weight    |       0xb0003980 |        0x1810000 |
+|  263 | blk.28.ffn_norm.weight    |       0xb1813980 |           0x4000 |
+|  264 | blk.28.ffn_up.weight      |       0xb1817980 |        0x1810000 |
+|  265 | blk.29.attn_k.weight      |       0xb3027980 |         0x1b8000 |
+|  266 | blk.29.attn_norm.weight   |       0xb31df980 |           0x4000 |
+|  267 | blk.29.attn_output.weight |       0xb31e3980 |         0x6e0000 |
+|  268 | blk.29.attn_q.weight      |       0xb38c3980 |         0x6e0000 |
+|  269 | blk.29.attn_v.weight      |       0xb3fa3980 |         0x1b8000 |
+|  270 | blk.29.ffn_down.weight    |       0xb415b980 |        0x1f80000 |
+|  271 | blk.29.ffn_gate.weight    |       0xb60db980 |        0x1810000 |
+|  272 | blk.29.ffn_norm.weight    |       0xb78eb980 |           0x4000 |
+|  273 | blk.29.ffn_up.weight      |       0xb78ef980 |        0x1810000 |
+|  274 | blk.30.attn_k.weight      |       0xb90ff980 |         0x1b8000 |
+|  275 | blk.30.attn_norm.weight   |       0xb92b7980 |           0x4000 |
+|  276 | blk.30.attn_output.weight |       0xb92bb980 |         0x6e0000 |
+|  277 | blk.30.attn_q.weight      |       0xb999b980 |         0x6e0000 |
+|  278 | blk.30.attn_v.weight      |       0xba07b980 |         0x1b8000 |
+|  279 | blk.30.ffn_down.weight    |       0xba233980 |        0x1f80000 |
+|  280 | blk.30.ffn_gate.weight    |       0xbc1b3980 |        0x1810000 |
+|  281 | blk.30.ffn_norm.weight    |       0xbd9c3980 |           0x4000 |
+|  282 | blk.30.ffn_up.weight      |       0xbd9c7980 |        0x1810000 |
+|  283 | blk.31.attn_k.weight      |       0xbf1d7980 |         0x150000 |
+|  284 | blk.31.attn_norm.weight   |       0xbf327980 |           0x4000 |
+|  285 | blk.31.attn_output.weight |       0xbf32b980 |         0x6e0000 |
+|  286 | blk.31.attn_q.weight      |       0xbfa0b980 |         0x540000 |
+|  287 | blk.31.attn_v.weight      |       0xbff4b980 |         0x1b8000 |
+|  288 | blk.31.ffn_down.weight    |       0xc0103980 |        0x1f80000 |
+|  289 | blk.31.ffn_gate.weight    |       0xc2083980 |        0x1810000 |
+|  290 | blk.31.ffn_norm.weight    |       0xc3893980 |           0x4000 |
+|  291 | blk.31.ffn_up.weight      |       0xc3897980 |        0x1810000 |
+### <a name="base">Base Tensor Group : ~1B Elements</a>
+| T_ID | Tensor Layer Name  | Human Friendly Tensor Layer Name | Elements          | Shape                 | Type |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
+|    0 | output.weight      | Output (W)                       | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q3_K |
+|    1 | output_norm.weight | Output Normalization (W)         | (  ~4K)      4096 | 4096 x      1 x 1 x 1 | F32  |
+|    2 | rope_freqs.weight  | Rope_Freqs (W)                   | (   64)        64 |   64 x      1 x 1 x 1 | F32  |
+|    3 | token_embd.weight  | Token Embedding (W)              | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q2_K |
+- Total elements in base: ( ~1B) 1050677312
+- Percentage of total elements: 13.08%
+### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|    4 | blk.0.attn_k.weight      | Block 0 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|    5 | blk.0.attn_norm.weight   | Block 0 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|    6 | blk.0.attn_output.weight | Block 0 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|    7 | blk.0.attn_q.weight      | Block 0 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|    8 | blk.0.attn_v.weight      | Block 0 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|    9 | blk.0.ffn_down.weight    | Block 0 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|   10 | blk.0.ffn_gate.weight    | Block 0 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   11 | blk.0.ffn_norm.weight    | Block 0 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   12 | blk.0.ffn_up.weight      | Block 0 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.0: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   13 | blk.1.attn_k.weight      | Block 1 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   14 | blk.1.attn_norm.weight   | Block 1 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   15 | blk.1.attn_output.weight | Block 1 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   16 | blk.1.attn_q.weight      | Block 1 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   17 | blk.1.attn_v.weight      | Block 1 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   18 | blk.1.ffn_down.weight    | Block 1 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   19 | blk.1.ffn_gate.weight    | Block 1 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   20 | blk.1.ffn_norm.weight    | Block 1 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   21 | blk.1.ffn_up.weight      | Block 1 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.1: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   22 | blk.2.attn_k.weight      | Block 2 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   23 | blk.2.attn_norm.weight   | Block 2 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   24 | blk.2.attn_output.weight | Block 2 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   25 | blk.2.attn_q.weight      | Block 2 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   26 | blk.2.attn_v.weight      | Block 2 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   27 | blk.2.ffn_down.weight    | Block 2 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|   28 | blk.2.ffn_gate.weight    | Block 2 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   29 | blk.2.ffn_norm.weight    | Block 2 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   30 | blk.2.ffn_up.weight      | Block 2 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.2: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   31 | blk.3.attn_k.weight      | Block 3 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   32 | blk.3.attn_norm.weight   | Block 3 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   33 | blk.3.attn_output.weight | Block 3 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   34 | blk.3.attn_q.weight      | Block 3 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   35 | blk.3.attn_v.weight      | Block 3 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   36 | blk.3.ffn_down.weight    | Block 3 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|   37 | blk.3.ffn_gate.weight    | Block 3 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   38 | blk.3.ffn_norm.weight    | Block 3 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   39 | blk.3.ffn_up.weight      | Block 3 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.3: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   40 | blk.4.attn_k.weight      | Block 4 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   41 | blk.4.attn_norm.weight   | Block 4 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   42 | blk.4.attn_output.weight | Block 4 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   43 | blk.4.attn_q.weight      | Block 4 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   44 | blk.4.attn_v.weight      | Block 4 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   45 | blk.4.ffn_down.weight    | Block 4 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|   46 | blk.4.ffn_gate.weight    | Block 4 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   47 | blk.4.ffn_norm.weight    | Block 4 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   48 | blk.4.ffn_up.weight      | Block 4 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.4: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   49 | blk.5.attn_k.weight      | Block 5 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   50 | blk.5.attn_norm.weight   | Block 5 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   51 | blk.5.attn_output.weight | Block 5 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   52 | blk.5.attn_q.weight      | Block 5 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   53 | blk.5.attn_v.weight      | Block 5 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   54 | blk.5.ffn_down.weight    | Block 5 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|   55 | blk.5.ffn_gate.weight    | Block 5 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   56 | blk.5.ffn_norm.weight    | Block 5 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   57 | blk.5.ffn_up.weight      | Block 5 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.5: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   58 | blk.6.attn_k.weight      | Block 6 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   59 | blk.6.attn_norm.weight   | Block 6 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   60 | blk.6.attn_output.weight | Block 6 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   61 | blk.6.attn_q.weight      | Block 6 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   62 | blk.6.attn_v.weight      | Block 6 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   63 | blk.6.ffn_down.weight    | Block 6 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|   64 | blk.6.ffn_gate.weight    | Block 6 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   65 | blk.6.ffn_norm.weight    | Block 6 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   66 | blk.6.ffn_up.weight      | Block 6 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.6: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   67 | blk.7.attn_k.weight      | Block 7 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   68 | blk.7.attn_norm.weight   | Block 7 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   69 | blk.7.attn_output.weight | Block 7 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   70 | blk.7.attn_q.weight      | Block 7 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   71 | blk.7.attn_v.weight      | Block 7 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   72 | blk.7.ffn_down.weight    | Block 7 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|   73 | blk.7.ffn_gate.weight    | Block 7 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   74 | blk.7.ffn_norm.weight    | Block 7 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   75 | blk.7.ffn_up.weight      | Block 7 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.7: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   76 | blk.8.attn_k.weight      | Block 8 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   77 | blk.8.attn_norm.weight   | Block 8 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   78 | blk.8.attn_output.weight | Block 8 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   79 | blk.8.attn_q.weight      | Block 8 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   80 | blk.8.attn_v.weight      | Block 8 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   81 | blk.8.ffn_down.weight    | Block 8 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|   82 | blk.8.ffn_gate.weight    | Block 8 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   83 | blk.8.ffn_norm.weight    | Block 8 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   84 | blk.8.ffn_up.weight      | Block 8 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.8: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   85 | blk.9.attn_k.weight      | Block 9 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   86 | blk.9.attn_norm.weight   | Block 9 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   87 | blk.9.attn_output.weight | Block 9 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   88 | blk.9.attn_q.weight      | Block 9 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   89 | blk.9.attn_v.weight      | Block 9 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   90 | blk.9.ffn_down.weight    | Block 9 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|   91 | blk.9.ffn_gate.weight    | Block 9 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|   92 | blk.9.ffn_norm.weight    | Block 9 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   93 | blk.9.ffn_up.weight      | Block 9 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.9: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|   94 | blk.10.attn_k.weight      | Block 10 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|   95 | blk.10.attn_norm.weight   | Block 10 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   96 | blk.10.attn_output.weight | Block 10 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   97 | blk.10.attn_q.weight      | Block 10 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|   98 | blk.10.attn_v.weight      | Block 10 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   99 | blk.10.ffn_down.weight    | Block 10 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|  100 | blk.10.ffn_gate.weight    | Block 10 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  101 | blk.10.ffn_norm.weight    | Block 10 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  102 | blk.10.ffn_up.weight      | Block 10 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.10: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  103 | blk.11.attn_k.weight      | Block 11 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  104 | blk.11.attn_norm.weight   | Block 11 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  105 | blk.11.attn_output.weight | Block 11 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  106 | blk.11.attn_q.weight      | Block 11 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  107 | blk.11.attn_v.weight      | Block 11 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  108 | blk.11.ffn_down.weight    | Block 11 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|  109 | blk.11.ffn_gate.weight    | Block 11 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  110 | blk.11.ffn_norm.weight    | Block 11 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  111 | blk.11.ffn_up.weight      | Block 11 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.11: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  112 | blk.12.attn_k.weight      | Block 12 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  113 | blk.12.attn_norm.weight   | Block 12 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  114 | blk.12.attn_output.weight | Block 12 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  115 | blk.12.attn_q.weight      | Block 12 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  116 | blk.12.attn_v.weight      | Block 12 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  117 | blk.12.ffn_down.weight    | Block 12 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|  118 | blk.12.ffn_gate.weight    | Block 12 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  119 | blk.12.ffn_norm.weight    | Block 12 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  120 | blk.12.ffn_up.weight      | Block 12 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.12: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  121 | blk.13.attn_k.weight      | Block 13 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  122 | blk.13.attn_norm.weight   | Block 13 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  123 | blk.13.attn_output.weight | Block 13 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  124 | blk.13.attn_q.weight      | Block 13 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  125 | blk.13.attn_v.weight      | Block 13 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  126 | blk.13.ffn_down.weight    | Block 13 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|  127 | blk.13.ffn_gate.weight    | Block 13 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  128 | blk.13.ffn_norm.weight    | Block 13 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  129 | blk.13.ffn_up.weight      | Block 13 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.13: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  130 | blk.14.attn_k.weight      | Block 14 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  131 | blk.14.attn_norm.weight   | Block 14 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  132 | blk.14.attn_output.weight | Block 14 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  133 | blk.14.attn_q.weight      | Block 14 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  134 | blk.14.attn_v.weight      | Block 14 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  135 | blk.14.ffn_down.weight    | Block 14 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|  136 | blk.14.ffn_gate.weight    | Block 14 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  137 | blk.14.ffn_norm.weight    | Block 14 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  138 | blk.14.ffn_up.weight      | Block 14 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.14: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  139 | blk.15.attn_k.weight      | Block 15 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  140 | blk.15.attn_norm.weight   | Block 15 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  141 | blk.15.attn_output.weight | Block 15 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  142 | blk.15.attn_q.weight      | Block 15 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  143 | blk.15.attn_v.weight      | Block 15 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  144 | blk.15.ffn_down.weight    | Block 15 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|  145 | blk.15.ffn_gate.weight    | Block 15 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+|  146 | blk.15.ffn_norm.weight    | Block 15 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  147 | blk.15.ffn_up.weight      | Block 15 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q2_K |
+- Total elements in blk.15: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  148 | blk.16.attn_k.weight      | Block 16 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  149 | blk.16.attn_norm.weight   | Block 16 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  150 | blk.16.attn_output.weight | Block 16 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  151 | blk.16.attn_q.weight      | Block 16 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  152 | blk.16.attn_v.weight      | Block 16 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  153 | blk.16.ffn_down.weight    | Block 16 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q3_K |
+|  154 | blk.16.ffn_gate.weight    | Block 16 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  155 | blk.16.ffn_norm.weight    | Block 16 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  156 | blk.16.ffn_up.weight      | Block 16 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.16: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  157 | blk.17.attn_k.weight      | Block 17 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  158 | blk.17.attn_norm.weight   | Block 17 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  159 | blk.17.attn_output.weight | Block 17 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  160 | blk.17.attn_q.weight      | Block 17 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  161 | blk.17.attn_v.weight      | Block 17 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  162 | blk.17.ffn_down.weight    | Block 17 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  163 | blk.17.ffn_gate.weight    | Block 17 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  164 | blk.17.ffn_norm.weight    | Block 17 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  165 | blk.17.ffn_up.weight      | Block 17 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.17: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  166 | blk.18.attn_k.weight      | Block 18 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  167 | blk.18.attn_norm.weight   | Block 18 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  168 | blk.18.attn_output.weight | Block 18 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  169 | blk.18.attn_q.weight      | Block 18 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  170 | blk.18.attn_v.weight      | Block 18 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  171 | blk.18.ffn_down.weight    | Block 18 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  172 | blk.18.ffn_gate.weight    | Block 18 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  173 | blk.18.ffn_norm.weight    | Block 18 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  174 | blk.18.ffn_up.weight      | Block 18 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.18: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  175 | blk.19.attn_k.weight      | Block 19 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  176 | blk.19.attn_norm.weight   | Block 19 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  177 | blk.19.attn_output.weight | Block 19 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  178 | blk.19.attn_q.weight      | Block 19 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  179 | blk.19.attn_v.weight      | Block 19 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  180 | blk.19.ffn_down.weight    | Block 19 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  181 | blk.19.ffn_gate.weight    | Block 19 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  182 | blk.19.ffn_norm.weight    | Block 19 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  183 | blk.19.ffn_up.weight      | Block 19 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.19: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  184 | blk.20.attn_k.weight      | Block 20 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  185 | blk.20.attn_norm.weight   | Block 20 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  186 | blk.20.attn_output.weight | Block 20 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  187 | blk.20.attn_q.weight      | Block 20 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  188 | blk.20.attn_v.weight      | Block 20 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  189 | blk.20.ffn_down.weight    | Block 20 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  190 | blk.20.ffn_gate.weight    | Block 20 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  191 | blk.20.ffn_norm.weight    | Block 20 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  192 | blk.20.ffn_up.weight      | Block 20 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.20: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  193 | blk.21.attn_k.weight      | Block 21 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  194 | blk.21.attn_norm.weight   | Block 21 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  195 | blk.21.attn_output.weight | Block 21 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  196 | blk.21.attn_q.weight      | Block 21 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  197 | blk.21.attn_v.weight      | Block 21 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  198 | blk.21.ffn_down.weight    | Block 21 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  199 | blk.21.ffn_gate.weight    | Block 21 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  200 | blk.21.ffn_norm.weight    | Block 21 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  201 | blk.21.ffn_up.weight      | Block 21 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.21: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  202 | blk.22.attn_k.weight      | Block 22 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  203 | blk.22.attn_norm.weight   | Block 22 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  204 | blk.22.attn_output.weight | Block 22 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  205 | blk.22.attn_q.weight      | Block 22 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  206 | blk.22.attn_v.weight      | Block 22 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  207 | blk.22.ffn_down.weight    | Block 22 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  208 | blk.22.ffn_gate.weight    | Block 22 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  209 | blk.22.ffn_norm.weight    | Block 22 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  210 | blk.22.ffn_up.weight      | Block 22 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.22: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  211 | blk.23.attn_k.weight      | Block 23 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  212 | blk.23.attn_norm.weight   | Block 23 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  213 | blk.23.attn_output.weight | Block 23 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  214 | blk.23.attn_q.weight      | Block 23 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  215 | blk.23.attn_v.weight      | Block 23 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  216 | blk.23.ffn_down.weight    | Block 23 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  217 | blk.23.ffn_gate.weight    | Block 23 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  218 | blk.23.ffn_norm.weight    | Block 23 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  219 | blk.23.ffn_up.weight      | Block 23 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.23: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  220 | blk.24.attn_k.weight      | Block 24 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  221 | blk.24.attn_norm.weight   | Block 24 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  222 | blk.24.attn_output.weight | Block 24 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  223 | blk.24.attn_q.weight      | Block 24 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  224 | blk.24.attn_v.weight      | Block 24 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  225 | blk.24.ffn_down.weight    | Block 24 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  226 | blk.24.ffn_gate.weight    | Block 24 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  227 | blk.24.ffn_norm.weight    | Block 24 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  228 | blk.24.ffn_up.weight      | Block 24 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.24: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  229 | blk.25.attn_k.weight      | Block 25 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  230 | blk.25.attn_norm.weight   | Block 25 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  231 | blk.25.attn_output.weight | Block 25 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  232 | blk.25.attn_q.weight      | Block 25 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  233 | blk.25.attn_v.weight      | Block 25 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  234 | blk.25.ffn_down.weight    | Block 25 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  235 | blk.25.ffn_gate.weight    | Block 25 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  236 | blk.25.ffn_norm.weight    | Block 25 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  237 | blk.25.ffn_up.weight      | Block 25 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.25: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  238 | blk.26.attn_k.weight      | Block 26 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  239 | blk.26.attn_norm.weight   | Block 26 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  240 | blk.26.attn_output.weight | Block 26 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  241 | blk.26.attn_q.weight      | Block 26 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  242 | blk.26.attn_v.weight      | Block 26 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  243 | blk.26.ffn_down.weight    | Block 26 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  244 | blk.26.ffn_gate.weight    | Block 26 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  245 | blk.26.ffn_norm.weight    | Block 26 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  246 | blk.26.ffn_up.weight      | Block 26 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.26: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  247 | blk.27.attn_k.weight      | Block 27 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  248 | blk.27.attn_norm.weight   | Block 27 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  249 | blk.27.attn_output.weight | Block 27 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  250 | blk.27.attn_q.weight      | Block 27 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  251 | blk.27.attn_v.weight      | Block 27 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  252 | blk.27.ffn_down.weight    | Block 27 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  253 | blk.27.ffn_gate.weight    | Block 27 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  254 | blk.27.ffn_norm.weight    | Block 27 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  255 | blk.27.ffn_up.weight      | Block 27 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.27: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  256 | blk.28.attn_k.weight      | Block 28 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  257 | blk.28.attn_norm.weight   | Block 28 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  258 | blk.28.attn_output.weight | Block 28 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  259 | blk.28.attn_q.weight      | Block 28 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  260 | blk.28.attn_v.weight      | Block 28 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  261 | blk.28.ffn_down.weight    | Block 28 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  262 | blk.28.ffn_gate.weight    | Block 28 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  263 | blk.28.ffn_norm.weight    | Block 28 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  264 | blk.28.ffn_up.weight      | Block 28 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.28: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  265 | blk.29.attn_k.weight      | Block 29 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  266 | blk.29.attn_norm.weight   | Block 29 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  267 | blk.29.attn_output.weight | Block 29 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  268 | blk.29.attn_q.weight      | Block 29 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  269 | blk.29.attn_v.weight      | Block 29 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  270 | blk.29.ffn_down.weight    | Block 29 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  271 | blk.29.ffn_gate.weight    | Block 29 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  272 | blk.29.ffn_norm.weight    | Block 29 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  273 | blk.29.ffn_up.weight      | Block 29 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.29: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  274 | blk.30.attn_k.weight      | Block 30 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  275 | blk.30.attn_norm.weight   | Block 30 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  276 | blk.30.attn_output.weight | Block 30 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  277 | blk.30.attn_q.weight      | Block 30 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  278 | blk.30.attn_v.weight      | Block 30 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  279 | blk.30.ffn_down.weight    | Block 30 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  280 | blk.30.ffn_gate.weight    | Block 30 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  281 | blk.30.ffn_norm.weight    | Block 30 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  282 | blk.30.ffn_up.weight      | Block 30 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.30: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  283 | blk.31.attn_k.weight      | Block 31 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q2_K |
+|  284 | blk.31.attn_norm.weight   | Block 31 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  285 | blk.31.attn_output.weight | Block 31 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  286 | blk.31.attn_q.weight      | Block 31 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q2_K |
+|  287 | blk.31.attn_v.weight      | Block 31 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  288 | blk.31.ffn_down.weight    | Block 31 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  289 | blk.31.ffn_gate.weight    | Block 31 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  290 | blk.31.ffn_norm.weight    | Block 31 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  291 | blk.31.ffn_up.weight      | Block 31 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.31: (~218M) 218112000
+- Percentage of total elements: 2.72%

scores/Llama-Guard-3-8B-Q4_K_M.md ADDED Viewed

	@@ -0,0 +1,978 @@

+# Llama-Guard-3-8B-Q4_K_M.gguf - GGUF Internal File Dump
+- Endian: LITTLE endian
+## Key Value Metadata Store
+There are 39 key-value pairs in this file
+| POS | TYPE     |  Count | Key                                    | Value                                                               |
+|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
+|   1 | UINT32   |      1 | GGUF.version                           | 3                                                                   |
+|   2 | UINT64   |      1 | GGUF.tensor_count                      | 292                                                                 |
+|   3 | UINT64   |      1 | GGUF.kv_count                          | 36                                                                  |
+|   4 | STRING   |      1 | general.architecture                   | `llama`                                                             |
+|   5 | STRING   |      1 | general.type                           | `model`                                                             |
+|   6 | STRING   |      1 | general.name                           | `Llama Guard 3 8B`                                                  |
+|   7 | STRING   |      1 | general.basename                       | `Llama-Guard-3`                                                     |
+|   8 | STRING   |      1 | general.size_label                     | `8B`                                                                |
+|   9 | STRING   |      1 | general.license                        | `llama3.1`                                                          |
+|  10 | UINT32   |      1 | general.base_model.count               | 1                                                                   |
+|  11 | STRING   |      1 | general.base_model.0.name              | `Meta Llama 3.1 8B`                                                 |
+|  12 | STRING   |      1 | general.base_model.0.organization      | `Meta Llama`                                                        |
+|  13 | STRING   |      1 | general.base_model.0.repo_url          | `https://huggingface.co/meta-llama/Meta-Llama-3.1-8B`               |
+|  14 | [STRING] |      6 | general.tags                           | [ `facebook`, `meta`, `pytorch`, `llama`, `llama-3`, ... ]          |
+|  15 | [STRING] |      1 | general.languages                      | [ `en` ]                                                            |
+|  16 | UINT32   |      1 | llama.block_count                      | 32                                                                  |
+|  17 | UINT32   |      1 | llama.context_length                   | 131072                                                              |
+|  18 | UINT32   |      1 | llama.embedding_length                 | 4096                                                                |
+|  19 | UINT32   |      1 | llama.feed_forward_length              | 14336                                                               |
+|  20 | UINT32   |      1 | llama.attention.head_count             | 32                                                                  |
+|  21 | UINT32   |      1 | llama.attention.head_count_kv          | 8                                                                   |
+|  22 | FLOAT32  |      1 | llama.rope.freq_base                   | 500000.0                                                            |
+|  23 | FLOAT32  |      1 | llama.attention.layer_norm_rms_epsilon | 1e-05                                                               |
+|  24 | UINT32   |      1 | llama.vocab_size                       | 128256                                                              |
+|  25 | UINT32   |      1 | llama.rope.dimension_count             | 128                                                                 |
+|  26 | STRING   |      1 | tokenizer.ggml.model                   | `gpt2`                                                              |
+|  27 | STRING   |      1 | tokenizer.ggml.pre                     | `smaug-bpe`                                                         |
+|  28 | [STRING] | 128256 | tokenizer.ggml.tokens                  | [ `!`, `"`, `#`, `$`, `%`, ... ]                                    |
+|  29 | [INT32]  | 128256 | tokenizer.ggml.token_type              | [ 1, 1, 1, 1, 1, 1, 1, ... ]                                        |
+|  30 | [STRING] | 280147 | tokenizer.ggml.merges                  | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]                    |
+|  31 | UINT32   |      1 | tokenizer.ggml.bos_token_id            | 128000                                                              |
+|  32 | UINT32   |      1 | tokenizer.ggml.eos_token_id            | 128009                                                              |
+|  33 | STRING   |      1 | tokenizer.chat_template                | `{% if messages|length % 2 == 0`...`assistant<|end_header_id|>" }}` |
+|  34 | UINT32   |      1 | general.quantization_version           | 2                                                                   |
+|  35 | UINT32   |      1 | general.file_type                      | 15                                                                  |
+|  36 | STRING   |      1 | quantize.imatrix.file                  | `./imatrix/imatrix-Llama-Guard-3-8B-small.dat`                      |
+|  37 | STRING   |      1 | quantize.imatrix.dataset               | `../../datasets/imatrix/calibration_eur_small.txt`                  |
+|  38 | INT32    |      1 | quantize.imatrix.entries_count         | 224                                                                 |
+|  39 | INT32    |      1 | quantize.imatrix.chunks_count          | 962                                                                 |
+## Tensors Overview ~8B Elements
+Total number of elements in all tensors: 8030261312 Elements
+- [Llama-Guard-3-8B-Q4\_K\_M.gguf - GGUF Internal File Dump](#llama-guard-3-8b-q4_k_mgguf---gguf-internal-file-dump)
+  - [Key Value Metadata Store](#key-value-metadata-store)
+  - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
+    - [Tensor Data Offset](#tensor-data-offset)
+    - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
+    - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
+    - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
+    - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
+    - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
+    - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
+    - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
+    - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
+    - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
+    - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
+    - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
+    - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
+    - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
+    - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
+    - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
+    - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
+    - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
+    - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
+    - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
+    - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
+    - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
+    - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
+    - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
+    - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
+    - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
+    - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
+    - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
+    - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
+    - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
+    - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
+    - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
+    - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
+    - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
+### Tensor Data Offset
+This table contains the offset and data segment relative to start of file
+| T_ID | Tensor Layer Name         |  Data Offset (B) |    Data Size (B) |
+|-----:|:--------------------------|-----------------:|-----------------:|
+|    0 | output.weight             |         0x779880 |       0x119d0000 |
+|    1 | output_norm.weight        |       0x12149880 |           0x4000 |
+|    2 | rope_freqs.weight         |       0x1214d880 |            0x100 |
+|    3 | token_embd.weight         |       0x1214d980 |        0xd746000 |
+|    4 | blk.0.attn_k.weight       |       0x1f893980 |         0x1b8000 |
+|    5 | blk.0.attn_norm.weight    |       0x1fa4b980 |           0x4000 |
+|    6 | blk.0.attn_output.weight  |       0x1fa4f980 |         0x900000 |
+|    7 | blk.0.attn_q.weight       |       0x2034f980 |         0x6e0000 |
+|    8 | blk.0.attn_v.weight       |       0x20a2f980 |         0x240000 |
+|    9 | blk.0.ffn_down.weight     |       0x20c6f980 |        0x2680000 |
+|   10 | blk.0.ffn_gate.weight     |       0x232ef980 |        0x1810000 |
+|   11 | blk.0.ffn_norm.weight     |       0x24aff980 |           0x4000 |
+|   12 | blk.0.ffn_up.weight       |       0x24b03980 |        0x1810000 |
+|   13 | blk.1.attn_k.weight       |       0x26313980 |         0x1b8000 |
+|   14 | blk.1.attn_norm.weight    |       0x264cb980 |           0x4000 |
+|   15 | blk.1.attn_output.weight  |       0x264cf980 |         0x900000 |
+|   16 | blk.1.attn_q.weight       |       0x26dcf980 |         0x6e0000 |
+|   17 | blk.1.attn_v.weight       |       0x274af980 |         0x240000 |
+|   18 | blk.1.ffn_down.weight     |       0x276ef980 |        0x2680000 |
+|   19 | blk.1.ffn_gate.weight     |       0x29d6f980 |        0x1810000 |
+|   20 | blk.1.ffn_norm.weight     |       0x2b57f980 |           0x4000 |
+|   21 | blk.1.ffn_up.weight       |       0x2b583980 |        0x1810000 |
+|   22 | blk.2.attn_k.weight       |       0x2cd93980 |         0x1b8000 |
+|   23 | blk.2.attn_norm.weight    |       0x2cf4b980 |           0x4000 |
+|   24 | blk.2.attn_output.weight  |       0x2cf4f980 |         0x900000 |
+|   25 | blk.2.attn_q.weight       |       0x2d84f980 |         0x6e0000 |
+|   26 | blk.2.attn_v.weight       |       0x2df2f980 |         0x240000 |
+|   27 | blk.2.ffn_down.weight     |       0x2e16f980 |        0x2680000 |
+|   28 | blk.2.ffn_gate.weight     |       0x307ef980 |        0x1810000 |
+|   29 | blk.2.ffn_norm.weight     |       0x31fff980 |           0x4000 |
+|   30 | blk.2.ffn_up.weight       |       0x32003980 |        0x1810000 |
+|   31 | blk.3.attn_k.weight       |       0x33813980 |         0x1b8000 |
+|   32 | blk.3.attn_norm.weight    |       0x339cb980 |           0x4000 |
+|   33 | blk.3.attn_output.weight  |       0x339cf980 |         0x900000 |
+|   34 | blk.3.attn_q.weight       |       0x342cf980 |         0x6e0000 |
+|   35 | blk.3.attn_v.weight       |       0x349af980 |         0x240000 |
+|   36 | blk.3.ffn_down.weight     |       0x34bef980 |        0x2680000 |
+|   37 | blk.3.ffn_gate.weight     |       0x3726f980 |        0x1810000 |
+|   38 | blk.3.ffn_norm.weight     |       0x38a7f980 |           0x4000 |
+|   39 | blk.3.ffn_up.weight       |       0x38a83980 |        0x1810000 |
+|   40 | blk.4.attn_k.weight       |       0x3a293980 |         0x1b8000 |
+|   41 | blk.4.attn_norm.weight    |       0x3a44b980 |           0x4000 |
+|   42 | blk.4.attn_output.weight  |       0x3a44f980 |         0x900000 |
+|   43 | blk.4.attn_q.weight       |       0x3ad4f980 |         0x6e0000 |
+|   44 | blk.4.attn_v.weight       |       0x3b42f980 |         0x240000 |
+|   45 | blk.4.ffn_down.weight     |       0x3b66f980 |        0x2680000 |
+|   46 | blk.4.ffn_gate.weight     |       0x3dcef980 |        0x1810000 |
+|   47 | blk.4.ffn_norm.weight     |       0x3f4ff980 |           0x4000 |
+|   48 | blk.4.ffn_up.weight       |       0x3f503980 |        0x1810000 |
+|   49 | blk.5.attn_k.weight       |       0x40d13980 |         0x1b8000 |
+|   50 | blk.5.attn_norm.weight    |       0x40ecb980 |           0x4000 |
+|   51 | blk.5.attn_output.weight  |       0x40ecf980 |         0x900000 |
+|   52 | blk.5.attn_q.weight       |       0x417cf980 |         0x6e0000 |
+|   53 | blk.5.attn_v.weight       |       0x41eaf980 |         0x240000 |
+|   54 | blk.5.ffn_down.weight     |       0x420ef980 |        0x2680000 |
+|   55 | blk.5.ffn_gate.weight     |       0x4476f980 |        0x1810000 |
+|   56 | blk.5.ffn_norm.weight     |       0x45f7f980 |           0x4000 |
+|   57 | blk.5.ffn_up.weight       |       0x45f83980 |        0x1810000 |
+|   58 | blk.6.attn_k.weight       |       0x47793980 |         0x1b8000 |
+|   59 | blk.6.attn_norm.weight    |       0x4794b980 |           0x4000 |
+|   60 | blk.6.attn_output.weight  |       0x4794f980 |         0x900000 |
+|   61 | blk.6.attn_q.weight       |       0x4824f980 |         0x6e0000 |
+|   62 | blk.6.attn_v.weight       |       0x4892f980 |         0x240000 |
+|   63 | blk.6.ffn_down.weight     |       0x48b6f980 |        0x2680000 |
+|   64 | blk.6.ffn_gate.weight     |       0x4b1ef980 |        0x1810000 |
+|   65 | blk.6.ffn_norm.weight     |       0x4c9ff980 |           0x4000 |
+|   66 | blk.6.ffn_up.weight       |       0x4ca03980 |        0x1810000 |
+|   67 | blk.7.attn_k.weight       |       0x4e213980 |         0x1b8000 |
+|   68 | blk.7.attn_norm.weight    |       0x4e3cb980 |           0x4000 |
+|   69 | blk.7.attn_output.weight  |       0x4e3cf980 |         0x900000 |
+|   70 | blk.7.attn_q.weight       |       0x4eccf980 |         0x6e0000 |
+|   71 | blk.7.attn_v.weight       |       0x4f3af980 |         0x240000 |
+|   72 | blk.7.ffn_down.weight     |       0x4f5ef980 |        0x2680000 |
+|   73 | blk.7.ffn_gate.weight     |       0x51c6f980 |        0x1810000 |
+|   74 | blk.7.ffn_norm.weight     |       0x5347f980 |           0x4000 |
+|   75 | blk.7.ffn_up.weight       |       0x53483980 |        0x1810000 |
+|   76 | blk.8.attn_k.weight       |       0x54c93980 |         0x1b8000 |
+|   77 | blk.8.attn_norm.weight    |       0x54e4b980 |           0x4000 |
+|   78 | blk.8.attn_output.weight  |       0x54e4f980 |         0x900000 |
+|   79 | blk.8.attn_q.weight       |       0x5574f980 |         0x6e0000 |
+|   80 | blk.8.attn_v.weight       |       0x55e2f980 |         0x240000 |
+|   81 | blk.8.ffn_down.weight     |       0x5606f980 |        0x2680000 |
+|   82 | blk.8.ffn_gate.weight     |       0x586ef980 |        0x1810000 |
+|   83 | blk.8.ffn_norm.weight     |       0x59eff980 |           0x4000 |
+|   84 | blk.8.ffn_up.weight       |       0x59f03980 |        0x1810000 |
+|   85 | blk.9.attn_k.weight       |       0x5b713980 |         0x1b8000 |
+|   86 | blk.9.attn_norm.weight    |       0x5b8cb980 |           0x4000 |
+|   87 | blk.9.attn_output.weight  |       0x5b8cf980 |         0x900000 |
+|   88 | blk.9.attn_q.weight       |       0x5c1cf980 |         0x6e0000 |
+|   89 | blk.9.attn_v.weight       |       0x5c8af980 |         0x240000 |
+|   90 | blk.9.ffn_down.weight     |       0x5caef980 |        0x2680000 |
+|   91 | blk.9.ffn_gate.weight     |       0x5f16f980 |        0x1810000 |
+|   92 | blk.9.ffn_norm.weight     |       0x6097f980 |           0x4000 |
+|   93 | blk.9.ffn_up.weight       |       0x60983980 |        0x1810000 |
+|   94 | blk.10.attn_k.weight      |       0x62193980 |         0x1b8000 |
+|   95 | blk.10.attn_norm.weight   |       0x6234b980 |           0x4000 |
+|   96 | blk.10.attn_output.weight |       0x6234f980 |         0x900000 |
+|   97 | blk.10.attn_q.weight      |       0x62c4f980 |         0x6e0000 |
+|   98 | blk.10.attn_v.weight      |       0x6332f980 |         0x240000 |
+|   99 | blk.10.ffn_down.weight    |       0x6356f980 |        0x2680000 |
+|  100 | blk.10.ffn_gate.weight    |       0x65bef980 |        0x1810000 |
+|  101 | blk.10.ffn_norm.weight    |       0x673ff980 |           0x4000 |
+|  102 | blk.10.ffn_up.weight      |       0x67403980 |        0x1810000 |
+|  103 | blk.11.attn_k.weight      |       0x68c13980 |         0x1b8000 |
+|  104 | blk.11.attn_norm.weight   |       0x68dcb980 |           0x4000 |
+|  105 | blk.11.attn_output.weight |       0x68dcf980 |         0x900000 |
+|  106 | blk.11.attn_q.weight      |       0x696cf980 |         0x6e0000 |
+|  107 | blk.11.attn_v.weight      |       0x69daf980 |         0x240000 |
+|  108 | blk.11.ffn_down.weight    |       0x69fef980 |        0x2680000 |
+|  109 | blk.11.ffn_gate.weight    |       0x6c66f980 |        0x1810000 |
+|  110 | blk.11.ffn_norm.weight    |       0x6de7f980 |           0x4000 |
+|  111 | blk.11.ffn_up.weight      |       0x6de83980 |        0x1810000 |
+|  112 | blk.12.attn_k.weight      |       0x6f693980 |         0x1b8000 |
+|  113 | blk.12.attn_norm.weight   |       0x6f84b980 |           0x4000 |
+|  114 | blk.12.attn_output.weight |       0x6f84f980 |         0x900000 |
+|  115 | blk.12.attn_q.weight      |       0x7014f980 |         0x6e0000 |
+|  116 | blk.12.attn_v.weight      |       0x7082f980 |         0x240000 |
+|  117 | blk.12.ffn_down.weight    |       0x70a6f980 |        0x2680000 |
+|  118 | blk.12.ffn_gate.weight    |       0x730ef980 |        0x1810000 |
+|  119 | blk.12.ffn_norm.weight    |       0x748ff980 |           0x4000 |
+|  120 | blk.12.ffn_up.weight      |       0x74903980 |        0x1810000 |
+|  121 | blk.13.attn_k.weight      |       0x76113980 |         0x240000 |
+|  122 | blk.13.attn_norm.weight   |       0x76353980 |           0x4000 |
+|  123 | blk.13.attn_output.weight |       0x76357980 |         0x900000 |
+|  124 | blk.13.attn_q.weight      |       0x76c57980 |         0x900000 |
+|  125 | blk.13.attn_v.weight      |       0x77557980 |         0x2c0000 |
+|  126 | blk.13.ffn_down.weight    |       0x77817980 |        0x2680000 |
+|  127 | blk.13.ffn_gate.weight    |       0x79e97980 |        0x1810000 |
+|  128 | blk.13.ffn_norm.weight    |       0x7b6a7980 |           0x4000 |
+|  129 | blk.13.ffn_up.weight      |       0x7b6ab980 |        0x1810000 |
+|  130 | blk.14.attn_k.weight      |       0x7cebb980 |         0x240000 |
+|  131 | blk.14.attn_norm.weight   |       0x7d0fb980 |           0x4000 |
+|  132 | blk.14.attn_output.weight |       0x7d0ff980 |         0x900000 |
+|  133 | blk.14.attn_q.weight      |       0x7d9ff980 |         0x900000 |
+|  134 | blk.14.attn_v.weight      |       0x7e2ff980 |         0x2c0000 |
+|  135 | blk.14.ffn_down.weight    |       0x7e5bf980 |        0x2680000 |
+|  136 | blk.14.ffn_gate.weight    |       0x80c3f980 |        0x1810000 |
+|  137 | blk.14.ffn_norm.weight    |       0x8244f980 |           0x4000 |
+|  138 | blk.14.ffn_up.weight      |       0x82453980 |        0x1810000 |
+|  139 | blk.15.attn_k.weight      |       0x83c63980 |         0x1b8000 |
+|  140 | blk.15.attn_norm.weight   |       0x83e1b980 |           0x4000 |
+|  141 | blk.15.attn_output.weight |       0x83e1f980 |         0x900000 |
+|  142 | blk.15.attn_q.weight      |       0x8471f980 |         0x6e0000 |
+|  143 | blk.15.attn_v.weight      |       0x84dff980 |         0x240000 |
+|  144 | blk.15.ffn_down.weight    |       0x8503f980 |        0x2680000 |
+|  145 | blk.15.ffn_gate.weight    |       0x876bf980 |        0x1810000 |
+|  146 | blk.15.ffn_norm.weight    |       0x88ecf980 |           0x4000 |
+|  147 | blk.15.ffn_up.weight      |       0x88ed3980 |        0x1810000 |
+|  148 | blk.16.attn_k.weight      |       0x8a6e3980 |         0x240000 |
+|  149 | blk.16.attn_norm.weight   |       0x8a923980 |           0x4000 |
+|  150 | blk.16.attn_output.weight |       0x8a927980 |         0x900000 |
+|  151 | blk.16.attn_q.weight      |       0x8b227980 |         0x900000 |
+|  152 | blk.16.attn_v.weight      |       0x8bb27980 |         0x2c0000 |
+|  153 | blk.16.ffn_down.weight    |       0x8bde7980 |        0x2680000 |
+|  154 | blk.16.ffn_gate.weight    |       0x8e467980 |        0x1f80000 |
+|  155 | blk.16.ffn_norm.weight    |       0x903e7980 |           0x4000 |
+|  156 | blk.16.ffn_up.weight      |       0x903eb980 |        0x1f80000 |
+|  157 | blk.17.attn_k.weight      |       0x9236b980 |         0x1b8000 |
+|  158 | blk.17.attn_norm.weight   |       0x92523980 |           0x4000 |
+|  159 | blk.17.attn_output.weight |       0x92527980 |         0x900000 |
+|  160 | blk.17.attn_q.weight      |       0x92e27980 |         0x6e0000 |
+|  161 | blk.17.attn_v.weight      |       0x93507980 |         0x240000 |
+|  162 | blk.17.ffn_down.weight    |       0x93747980 |        0x2680000 |
+|  163 | blk.17.ffn_gate.weight    |       0x95dc7980 |        0x1f80000 |
+|  164 | blk.17.ffn_norm.weight    |       0x97d47980 |           0x4000 |
+|  165 | blk.17.ffn_up.weight      |       0x97d4b980 |        0x1f80000 |
+|  166 | blk.18.attn_k.weight      |       0x99ccb980 |         0x240000 |
+|  167 | blk.18.attn_norm.weight   |       0x99f0b980 |           0x4000 |
+|  168 | blk.18.attn_output.weight |       0x99f0f980 |         0x900000 |
+|  169 | blk.18.attn_q.weight      |       0x9a80f980 |         0x900000 |
+|  170 | blk.18.attn_v.weight      |       0x9b10f980 |         0x2c0000 |
+|  171 | blk.18.ffn_down.weight    |       0x9b3cf980 |        0x2680000 |
+|  172 | blk.18.ffn_gate.weight    |       0x9da4f980 |        0x1f80000 |
+|  173 | blk.18.ffn_norm.weight    |       0x9f9cf980 |           0x4000 |
+|  174 | blk.18.ffn_up.weight      |       0x9f9d3980 |        0x1f80000 |
+|  175 | blk.19.attn_k.weight      |       0xa1953980 |         0x240000 |
+|  176 | blk.19.attn_norm.weight   |       0xa1b93980 |           0x4000 |
+|  177 | blk.19.attn_output.weight |       0xa1b97980 |         0x900000 |
+|  178 | blk.19.attn_q.weight      |       0xa2497980 |         0x900000 |
+|  179 | blk.19.attn_v.weight      |       0xa2d97980 |         0x2c0000 |
+|  180 | blk.19.ffn_down.weight    |       0xa3057980 |        0x2680000 |
+|  181 | blk.19.ffn_gate.weight    |       0xa56d7980 |        0x1f80000 |
+|  182 | blk.19.ffn_norm.weight    |       0xa7657980 |           0x4000 |
+|  183 | blk.19.ffn_up.weight      |       0xa765b980 |        0x1f80000 |
+|  184 | blk.20.attn_k.weight      |       0xa95db980 |         0x240000 |
+|  185 | blk.20.attn_norm.weight   |       0xa981b980 |           0x4000 |
+|  186 | blk.20.attn_output.weight |       0xa981f980 |         0x900000 |
+|  187 | blk.20.attn_q.weight      |       0xaa11f980 |         0x900000 |
+|  188 | blk.20.attn_v.weight      |       0xaaa1f980 |         0x2c0000 |
+|  189 | blk.20.ffn_down.weight    |       0xaacdf980 |        0x2680000 |
+|  190 | blk.20.ffn_gate.weight    |       0xad35f980 |        0x1f80000 |
+|  191 | blk.20.ffn_norm.weight    |       0xaf2df980 |           0x4000 |
+|  192 | blk.20.ffn_up.weight      |       0xaf2e3980 |        0x1f80000 |
+|  193 | blk.21.attn_k.weight      |       0xb1263980 |         0x240000 |
+|  194 | blk.21.attn_norm.weight   |       0xb14a3980 |           0x4000 |
+|  195 | blk.21.attn_output.weight |       0xb14a7980 |         0x900000 |
+|  196 | blk.21.attn_q.weight      |       0xb1da7980 |         0x900000 |
+|  197 | blk.21.attn_v.weight      |       0xb26a7980 |         0x2c0000 |
+|  198 | blk.21.ffn_down.weight    |       0xb2967980 |        0x2680000 |
+|  199 | blk.21.ffn_gate.weight    |       0xb4fe7980 |        0x1f80000 |
+|  200 | blk.21.ffn_norm.weight    |       0xb6f67980 |           0x4000 |
+|  201 | blk.21.ffn_up.weight      |       0xb6f6b980 |        0x1f80000 |
+|  202 | blk.22.attn_k.weight      |       0xb8eeb980 |         0x240000 |
+|  203 | blk.22.attn_norm.weight   |       0xb912b980 |           0x4000 |
+|  204 | blk.22.attn_output.weight |       0xb912f980 |         0x900000 |
+|  205 | blk.22.attn_q.weight      |       0xb9a2f980 |         0x900000 |
+|  206 | blk.22.attn_v.weight      |       0xba32f980 |         0x2c0000 |
+|  207 | blk.22.ffn_down.weight    |       0xba5ef980 |        0x2680000 |
+|  208 | blk.22.ffn_gate.weight    |       0xbcc6f980 |        0x1f80000 |
+|  209 | blk.22.ffn_norm.weight    |       0xbebef980 |           0x4000 |
+|  210 | blk.22.ffn_up.weight      |       0xbebf3980 |        0x1f80000 |
+|  211 | blk.23.attn_k.weight      |       0xc0b73980 |         0x240000 |
+|  212 | blk.23.attn_norm.weight   |       0xc0db3980 |           0x4000 |
+|  213 | blk.23.attn_output.weight |       0xc0db7980 |         0x900000 |
+|  214 | blk.23.attn_q.weight      |       0xc16b7980 |         0x900000 |
+|  215 | blk.23.attn_v.weight      |       0xc1fb7980 |         0x2c0000 |
+|  216 | blk.23.ffn_down.weight    |       0xc2277980 |        0x2680000 |
+|  217 | blk.23.ffn_gate.weight    |       0xc48f7980 |        0x1f80000 |
+|  218 | blk.23.ffn_norm.weight    |       0xc6877980 |           0x4000 |
+|  219 | blk.23.ffn_up.weight      |       0xc687b980 |        0x1f80000 |
+|  220 | blk.24.attn_k.weight      |       0xc87fb980 |         0x240000 |
+|  221 | blk.24.attn_norm.weight   |       0xc8a3b980 |           0x4000 |
+|  222 | blk.24.attn_output.weight |       0xc8a3f980 |         0x900000 |
+|  223 | blk.24.attn_q.weight      |       0xc933f980 |         0x900000 |
+|  224 | blk.24.attn_v.weight      |       0xc9c3f980 |         0x2c0000 |
+|  225 | blk.24.ffn_down.weight    |       0xc9eff980 |        0x2680000 |
+|  226 | blk.24.ffn_gate.weight    |       0xcc57f980 |        0x1f80000 |
+|  227 | blk.24.ffn_norm.weight    |       0xce4ff980 |           0x4000 |
+|  228 | blk.24.ffn_up.weight      |       0xce503980 |        0x1f80000 |
+|  229 | blk.25.attn_k.weight      |       0xd0483980 |         0x240000 |
+|  230 | blk.25.attn_norm.weight   |       0xd06c3980 |           0x4000 |
+|  231 | blk.25.attn_output.weight |       0xd06c7980 |         0x900000 |
+|  232 | blk.25.attn_q.weight      |       0xd0fc7980 |         0x900000 |
+|  233 | blk.25.attn_v.weight      |       0xd18c7980 |         0x2c0000 |
+|  234 | blk.25.ffn_down.weight    |       0xd1b87980 |        0x2680000 |
+|  235 | blk.25.ffn_gate.weight    |       0xd4207980 |        0x1f80000 |
+|  236 | blk.25.ffn_norm.weight    |       0xd6187980 |           0x4000 |
+|  237 | blk.25.ffn_up.weight      |       0xd618b980 |        0x1f80000 |
+|  238 | blk.26.attn_k.weight      |       0xd810b980 |         0x240000 |
+|  239 | blk.26.attn_norm.weight   |       0xd834b980 |           0x4000 |
+|  240 | blk.26.attn_output.weight |       0xd834f980 |         0x900000 |
+|  241 | blk.26.attn_q.weight      |       0xd8c4f980 |         0x900000 |
+|  242 | blk.26.attn_v.weight      |       0xd954f980 |         0x2c0000 |
+|  243 | blk.26.ffn_down.weight    |       0xd980f980 |        0x2680000 |
+|  244 | blk.26.ffn_gate.weight    |       0xdbe8f980 |        0x1f80000 |
+|  245 | blk.26.ffn_norm.weight    |       0xdde0f980 |           0x4000 |
+|  246 | blk.26.ffn_up.weight      |       0xdde13980 |        0x1f80000 |
+|  247 | blk.27.attn_k.weight      |       0xdfd93980 |         0x240000 |
+|  248 | blk.27.attn_norm.weight   |       0xdffd3980 |           0x4000 |
+|  249 | blk.27.attn_output.weight |       0xdffd7980 |         0x900000 |
+|  250 | blk.27.attn_q.weight      |       0xe08d7980 |         0x900000 |
+|  251 | blk.27.attn_v.weight      |       0xe11d7980 |         0x2c0000 |
+|  252 | blk.27.ffn_down.weight    |       0xe1497980 |        0x2680000 |
+|  253 | blk.27.ffn_gate.weight    |       0xe3b17980 |        0x1f80000 |
+|  254 | blk.27.ffn_norm.weight    |       0xe5a97980 |           0x4000 |
+|  255 | blk.27.ffn_up.weight      |       0xe5a9b980 |        0x1f80000 |
+|  256 | blk.28.attn_k.weight      |       0xe7a1b980 |         0x240000 |
+|  257 | blk.28.attn_norm.weight   |       0xe7c5b980 |           0x4000 |
+|  258 | blk.28.attn_output.weight |       0xe7c5f980 |         0x900000 |
+|  259 | blk.28.attn_q.weight      |       0xe855f980 |         0x900000 |
+|  260 | blk.28.attn_v.weight      |       0xe8e5f980 |         0x2c0000 |
+|  261 | blk.28.ffn_down.weight    |       0xe911f980 |        0x2680000 |
+|  262 | blk.28.ffn_gate.weight    |       0xeb79f980 |        0x1f80000 |
+|  263 | blk.28.ffn_norm.weight    |       0xed71f980 |           0x4000 |
+|  264 | blk.28.ffn_up.weight      |       0xed723980 |        0x1f80000 |
+|  265 | blk.29.attn_k.weight      |       0xef6a3980 |         0x240000 |
+|  266 | blk.29.attn_norm.weight   |       0xef8e3980 |           0x4000 |
+|  267 | blk.29.attn_output.weight |       0xef8e7980 |         0x900000 |
+|  268 | blk.29.attn_q.weight      |       0xf01e7980 |         0x900000 |
+|  269 | blk.29.attn_v.weight      |       0xf0ae7980 |         0x2c0000 |
+|  270 | blk.29.ffn_down.weight    |       0xf0da7980 |        0x2680000 |
+|  271 | blk.29.ffn_gate.weight    |       0xf3427980 |        0x1f80000 |
+|  272 | blk.29.ffn_norm.weight    |       0xf53a7980 |           0x4000 |
+|  273 | blk.29.ffn_up.weight      |       0xf53ab980 |        0x1f80000 |
+|  274 | blk.30.attn_k.weight      |       0xf732b980 |         0x240000 |
+|  275 | blk.30.attn_norm.weight   |       0xf756b980 |           0x4000 |
+|  276 | blk.30.attn_output.weight |       0xf756f980 |         0x900000 |
+|  277 | blk.30.attn_q.weight      |       0xf7e6f980 |         0x900000 |
+|  278 | blk.30.attn_v.weight      |       0xf876f980 |         0x2c0000 |
+|  279 | blk.30.ffn_down.weight    |       0xf8a2f980 |        0x2680000 |
+|  280 | blk.30.ffn_gate.weight    |       0xfb0af980 |        0x1f80000 |
+|  281 | blk.30.ffn_norm.weight    |       0xfd02f980 |           0x4000 |
+|  282 | blk.30.ffn_up.weight      |       0xfd033980 |        0x1f80000 |
+|  283 | blk.31.attn_k.weight      |       0xfefb3980 |         0x1b8000 |
+|  284 | blk.31.attn_norm.weight   |       0xff16b980 |           0x4000 |
+|  285 | blk.31.attn_output.weight |       0xff16f980 |         0x900000 |
+|  286 | blk.31.attn_q.weight      |       0xffa6f980 |         0x6e0000 |
+|  287 | blk.31.attn_v.weight      |      0x10014f980 |         0x240000 |
+|  288 | blk.31.ffn_down.weight    |      0x10038f980 |        0x2680000 |
+|  289 | blk.31.ffn_gate.weight    |      0x102a0f980 |        0x1f80000 |
+|  290 | blk.31.ffn_norm.weight    |      0x10498f980 |           0x4000 |
+|  291 | blk.31.ffn_up.weight      |      0x104993980 |        0x1f80000 |
+### <a name="base">Base Tensor Group : ~1B Elements</a>
+| T_ID | Tensor Layer Name  | Human Friendly Tensor Layer Name | Elements          | Shape                 | Type |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
+|    0 | output.weight      | Output (W)                       | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q4_K |
+|    1 | output_norm.weight | Output Normalization (W)         | (  ~4K)      4096 | 4096 x      1 x 1 x 1 | F32  |
+|    2 | rope_freqs.weight  | Rope_Freqs (W)                   | (   64)        64 |   64 x      1 x 1 x 1 | F32  |
+|    3 | token_embd.weight  | Token Embedding (W)              | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q3_K |
+- Total elements in base: ( ~1B) 1050677312
+- Percentage of total elements: 13.08%
+### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|    4 | blk.0.attn_k.weight      | Block 0 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|    5 | blk.0.attn_norm.weight   | Block 0 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|    6 | blk.0.attn_output.weight | Block 0 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|    7 | blk.0.attn_q.weight      | Block 0 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|    8 | blk.0.attn_v.weight      | Block 0 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|    9 | blk.0.ffn_down.weight    | Block 0 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   10 | blk.0.ffn_gate.weight    | Block 0 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   11 | blk.0.ffn_norm.weight    | Block 0 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   12 | blk.0.ffn_up.weight      | Block 0 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.0: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   13 | blk.1.attn_k.weight      | Block 1 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   14 | blk.1.attn_norm.weight   | Block 1 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   15 | blk.1.attn_output.weight | Block 1 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   16 | blk.1.attn_q.weight      | Block 1 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   17 | blk.1.attn_v.weight      | Block 1 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   18 | blk.1.ffn_down.weight    | Block 1 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   19 | blk.1.ffn_gate.weight    | Block 1 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   20 | blk.1.ffn_norm.weight    | Block 1 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   21 | blk.1.ffn_up.weight      | Block 1 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.1: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   22 | blk.2.attn_k.weight      | Block 2 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   23 | blk.2.attn_norm.weight   | Block 2 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   24 | blk.2.attn_output.weight | Block 2 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   25 | blk.2.attn_q.weight      | Block 2 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   26 | blk.2.attn_v.weight      | Block 2 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   27 | blk.2.ffn_down.weight    | Block 2 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   28 | blk.2.ffn_gate.weight    | Block 2 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   29 | blk.2.ffn_norm.weight    | Block 2 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   30 | blk.2.ffn_up.weight      | Block 2 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.2: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   31 | blk.3.attn_k.weight      | Block 3 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   32 | blk.3.attn_norm.weight   | Block 3 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   33 | blk.3.attn_output.weight | Block 3 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   34 | blk.3.attn_q.weight      | Block 3 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   35 | blk.3.attn_v.weight      | Block 3 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   36 | blk.3.ffn_down.weight    | Block 3 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   37 | blk.3.ffn_gate.weight    | Block 3 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   38 | blk.3.ffn_norm.weight    | Block 3 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   39 | blk.3.ffn_up.weight      | Block 3 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.3: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   40 | blk.4.attn_k.weight      | Block 4 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   41 | blk.4.attn_norm.weight   | Block 4 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   42 | blk.4.attn_output.weight | Block 4 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   43 | blk.4.attn_q.weight      | Block 4 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   44 | blk.4.attn_v.weight      | Block 4 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   45 | blk.4.ffn_down.weight    | Block 4 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   46 | blk.4.ffn_gate.weight    | Block 4 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   47 | blk.4.ffn_norm.weight    | Block 4 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   48 | blk.4.ffn_up.weight      | Block 4 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.4: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   49 | blk.5.attn_k.weight      | Block 5 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   50 | blk.5.attn_norm.weight   | Block 5 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   51 | blk.5.attn_output.weight | Block 5 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   52 | blk.5.attn_q.weight      | Block 5 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   53 | blk.5.attn_v.weight      | Block 5 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   54 | blk.5.ffn_down.weight    | Block 5 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   55 | blk.5.ffn_gate.weight    | Block 5 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   56 | blk.5.ffn_norm.weight    | Block 5 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   57 | blk.5.ffn_up.weight      | Block 5 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.5: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   58 | blk.6.attn_k.weight      | Block 6 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   59 | blk.6.attn_norm.weight   | Block 6 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   60 | blk.6.attn_output.weight | Block 6 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   61 | blk.6.attn_q.weight      | Block 6 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   62 | blk.6.attn_v.weight      | Block 6 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   63 | blk.6.ffn_down.weight    | Block 6 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   64 | blk.6.ffn_gate.weight    | Block 6 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   65 | blk.6.ffn_norm.weight    | Block 6 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   66 | blk.6.ffn_up.weight      | Block 6 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.6: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   67 | blk.7.attn_k.weight      | Block 7 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   68 | blk.7.attn_norm.weight   | Block 7 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   69 | blk.7.attn_output.weight | Block 7 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   70 | blk.7.attn_q.weight      | Block 7 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   71 | blk.7.attn_v.weight      | Block 7 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   72 | blk.7.ffn_down.weight    | Block 7 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   73 | blk.7.ffn_gate.weight    | Block 7 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   74 | blk.7.ffn_norm.weight    | Block 7 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   75 | blk.7.ffn_up.weight      | Block 7 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.7: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   76 | blk.8.attn_k.weight      | Block 8 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   77 | blk.8.attn_norm.weight   | Block 8 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   78 | blk.8.attn_output.weight | Block 8 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   79 | blk.8.attn_q.weight      | Block 8 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   80 | blk.8.attn_v.weight      | Block 8 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   81 | blk.8.ffn_down.weight    | Block 8 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   82 | blk.8.ffn_gate.weight    | Block 8 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   83 | blk.8.ffn_norm.weight    | Block 8 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   84 | blk.8.ffn_up.weight      | Block 8 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.8: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   85 | blk.9.attn_k.weight      | Block 9 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   86 | blk.9.attn_norm.weight   | Block 9 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   87 | blk.9.attn_output.weight | Block 9 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   88 | blk.9.attn_q.weight      | Block 9 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   89 | blk.9.attn_v.weight      | Block 9 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   90 | blk.9.ffn_down.weight    | Block 9 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   91 | blk.9.ffn_gate.weight    | Block 9 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   92 | blk.9.ffn_norm.weight    | Block 9 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   93 | blk.9.ffn_up.weight      | Block 9 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.9: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|   94 | blk.10.attn_k.weight      | Block 10 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   95 | blk.10.attn_norm.weight   | Block 10 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   96 | blk.10.attn_output.weight | Block 10 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   97 | blk.10.attn_q.weight      | Block 10 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   98 | blk.10.attn_v.weight      | Block 10 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   99 | blk.10.ffn_down.weight    | Block 10 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  100 | blk.10.ffn_gate.weight    | Block 10 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  101 | blk.10.ffn_norm.weight    | Block 10 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  102 | blk.10.ffn_up.weight      | Block 10 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.10: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  103 | blk.11.attn_k.weight      | Block 11 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  104 | blk.11.attn_norm.weight   | Block 11 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  105 | blk.11.attn_output.weight | Block 11 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  106 | blk.11.attn_q.weight      | Block 11 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  107 | blk.11.attn_v.weight      | Block 11 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  108 | blk.11.ffn_down.weight    | Block 11 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  109 | blk.11.ffn_gate.weight    | Block 11 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  110 | blk.11.ffn_norm.weight    | Block 11 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  111 | blk.11.ffn_up.weight      | Block 11 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.11: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  112 | blk.12.attn_k.weight      | Block 12 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  113 | blk.12.attn_norm.weight   | Block 12 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  114 | blk.12.attn_output.weight | Block 12 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  115 | blk.12.attn_q.weight      | Block 12 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  116 | blk.12.attn_v.weight      | Block 12 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  117 | blk.12.ffn_down.weight    | Block 12 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  118 | blk.12.ffn_gate.weight    | Block 12 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  119 | blk.12.ffn_norm.weight    | Block 12 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  120 | blk.12.ffn_up.weight      | Block 12 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.12: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  121 | blk.13.attn_k.weight      | Block 13 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  122 | blk.13.attn_norm.weight   | Block 13 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  123 | blk.13.attn_output.weight | Block 13 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  124 | blk.13.attn_q.weight      | Block 13 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  125 | blk.13.attn_v.weight      | Block 13 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  126 | blk.13.ffn_down.weight    | Block 13 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  127 | blk.13.ffn_gate.weight    | Block 13 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  128 | blk.13.ffn_norm.weight    | Block 13 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  129 | blk.13.ffn_up.weight      | Block 13 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.13: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  130 | blk.14.attn_k.weight      | Block 14 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  131 | blk.14.attn_norm.weight   | Block 14 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  132 | blk.14.attn_output.weight | Block 14 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  133 | blk.14.attn_q.weight      | Block 14 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  134 | blk.14.attn_v.weight      | Block 14 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  135 | blk.14.ffn_down.weight    | Block 14 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  136 | blk.14.ffn_gate.weight    | Block 14 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  137 | blk.14.ffn_norm.weight    | Block 14 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  138 | blk.14.ffn_up.weight      | Block 14 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.14: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  139 | blk.15.attn_k.weight      | Block 15 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  140 | blk.15.attn_norm.weight   | Block 15 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  141 | blk.15.attn_output.weight | Block 15 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  142 | blk.15.attn_q.weight      | Block 15 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  143 | blk.15.attn_v.weight      | Block 15 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  144 | blk.15.ffn_down.weight    | Block 15 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  145 | blk.15.ffn_gate.weight    | Block 15 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  146 | blk.15.ffn_norm.weight    | Block 15 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  147 | blk.15.ffn_up.weight      | Block 15 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.15: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  148 | blk.16.attn_k.weight      | Block 16 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  149 | blk.16.attn_norm.weight   | Block 16 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  150 | blk.16.attn_output.weight | Block 16 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  151 | blk.16.attn_q.weight      | Block 16 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  152 | blk.16.attn_v.weight      | Block 16 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  153 | blk.16.ffn_down.weight    | Block 16 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  154 | blk.16.ffn_gate.weight    | Block 16 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  155 | blk.16.ffn_norm.weight    | Block 16 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  156 | blk.16.ffn_up.weight      | Block 16 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.16: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  157 | blk.17.attn_k.weight      | Block 17 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  158 | blk.17.attn_norm.weight   | Block 17 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  159 | blk.17.attn_output.weight | Block 17 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  160 | blk.17.attn_q.weight      | Block 17 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  161 | blk.17.attn_v.weight      | Block 17 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  162 | blk.17.ffn_down.weight    | Block 17 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  163 | blk.17.ffn_gate.weight    | Block 17 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  164 | blk.17.ffn_norm.weight    | Block 17 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  165 | blk.17.ffn_up.weight      | Block 17 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.17: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  166 | blk.18.attn_k.weight      | Block 18 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  167 | blk.18.attn_norm.weight   | Block 18 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  168 | blk.18.attn_output.weight | Block 18 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  169 | blk.18.attn_q.weight      | Block 18 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  170 | blk.18.attn_v.weight      | Block 18 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  171 | blk.18.ffn_down.weight    | Block 18 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  172 | blk.18.ffn_gate.weight    | Block 18 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  173 | blk.18.ffn_norm.weight    | Block 18 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  174 | blk.18.ffn_up.weight      | Block 18 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.18: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  175 | blk.19.attn_k.weight      | Block 19 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  176 | blk.19.attn_norm.weight   | Block 19 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  177 | blk.19.attn_output.weight | Block 19 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  178 | blk.19.attn_q.weight      | Block 19 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  179 | blk.19.attn_v.weight      | Block 19 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  180 | blk.19.ffn_down.weight    | Block 19 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  181 | blk.19.ffn_gate.weight    | Block 19 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  182 | blk.19.ffn_norm.weight    | Block 19 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  183 | blk.19.ffn_up.weight      | Block 19 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.19: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  184 | blk.20.attn_k.weight      | Block 20 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  185 | blk.20.attn_norm.weight   | Block 20 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  186 | blk.20.attn_output.weight | Block 20 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  187 | blk.20.attn_q.weight      | Block 20 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  188 | blk.20.attn_v.weight      | Block 20 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  189 | blk.20.ffn_down.weight    | Block 20 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  190 | blk.20.ffn_gate.weight    | Block 20 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  191 | blk.20.ffn_norm.weight    | Block 20 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  192 | blk.20.ffn_up.weight      | Block 20 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.20: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  193 | blk.21.attn_k.weight      | Block 21 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  194 | blk.21.attn_norm.weight   | Block 21 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  195 | blk.21.attn_output.weight | Block 21 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  196 | blk.21.attn_q.weight      | Block 21 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  197 | blk.21.attn_v.weight      | Block 21 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  198 | blk.21.ffn_down.weight    | Block 21 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  199 | blk.21.ffn_gate.weight    | Block 21 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  200 | blk.21.ffn_norm.weight    | Block 21 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  201 | blk.21.ffn_up.weight      | Block 21 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.21: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  202 | blk.22.attn_k.weight      | Block 22 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  203 | blk.22.attn_norm.weight   | Block 22 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  204 | blk.22.attn_output.weight | Block 22 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  205 | blk.22.attn_q.weight      | Block 22 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  206 | blk.22.attn_v.weight      | Block 22 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  207 | blk.22.ffn_down.weight    | Block 22 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  208 | blk.22.ffn_gate.weight    | Block 22 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  209 | blk.22.ffn_norm.weight    | Block 22 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  210 | blk.22.ffn_up.weight      | Block 22 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.22: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  211 | blk.23.attn_k.weight      | Block 23 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  212 | blk.23.attn_norm.weight   | Block 23 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  213 | blk.23.attn_output.weight | Block 23 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  214 | blk.23.attn_q.weight      | Block 23 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  215 | blk.23.attn_v.weight      | Block 23 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  216 | blk.23.ffn_down.weight    | Block 23 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  217 | blk.23.ffn_gate.weight    | Block 23 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  218 | blk.23.ffn_norm.weight    | Block 23 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  219 | blk.23.ffn_up.weight      | Block 23 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.23: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  220 | blk.24.attn_k.weight      | Block 24 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  221 | blk.24.attn_norm.weight   | Block 24 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  222 | blk.24.attn_output.weight | Block 24 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  223 | blk.24.attn_q.weight      | Block 24 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  224 | blk.24.attn_v.weight      | Block 24 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  225 | blk.24.ffn_down.weight    | Block 24 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  226 | blk.24.ffn_gate.weight    | Block 24 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  227 | blk.24.ffn_norm.weight    | Block 24 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  228 | blk.24.ffn_up.weight      | Block 24 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.24: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  229 | blk.25.attn_k.weight      | Block 25 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  230 | blk.25.attn_norm.weight   | Block 25 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  231 | blk.25.attn_output.weight | Block 25 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  232 | blk.25.attn_q.weight      | Block 25 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  233 | blk.25.attn_v.weight      | Block 25 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  234 | blk.25.ffn_down.weight    | Block 25 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  235 | blk.25.ffn_gate.weight    | Block 25 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  236 | blk.25.ffn_norm.weight    | Block 25 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  237 | blk.25.ffn_up.weight      | Block 25 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.25: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  238 | blk.26.attn_k.weight      | Block 26 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  239 | blk.26.attn_norm.weight   | Block 26 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  240 | blk.26.attn_output.weight | Block 26 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  241 | blk.26.attn_q.weight      | Block 26 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  242 | blk.26.attn_v.weight      | Block 26 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  243 | blk.26.ffn_down.weight    | Block 26 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  244 | blk.26.ffn_gate.weight    | Block 26 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  245 | blk.26.ffn_norm.weight    | Block 26 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  246 | blk.26.ffn_up.weight      | Block 26 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.26: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  247 | blk.27.attn_k.weight      | Block 27 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  248 | blk.27.attn_norm.weight   | Block 27 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  249 | blk.27.attn_output.weight | Block 27 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  250 | blk.27.attn_q.weight      | Block 27 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  251 | blk.27.attn_v.weight      | Block 27 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  252 | blk.27.ffn_down.weight    | Block 27 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  253 | blk.27.ffn_gate.weight    | Block 27 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  254 | blk.27.ffn_norm.weight    | Block 27 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  255 | blk.27.ffn_up.weight      | Block 27 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.27: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  256 | blk.28.attn_k.weight      | Block 28 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  257 | blk.28.attn_norm.weight   | Block 28 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  258 | blk.28.attn_output.weight | Block 28 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  259 | blk.28.attn_q.weight      | Block 28 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  260 | blk.28.attn_v.weight      | Block 28 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  261 | blk.28.ffn_down.weight    | Block 28 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  262 | blk.28.ffn_gate.weight    | Block 28 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  263 | blk.28.ffn_norm.weight    | Block 28 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  264 | blk.28.ffn_up.weight      | Block 28 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.28: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  265 | blk.29.attn_k.weight      | Block 29 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  266 | blk.29.attn_norm.weight   | Block 29 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  267 | blk.29.attn_output.weight | Block 29 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  268 | blk.29.attn_q.weight      | Block 29 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  269 | blk.29.attn_v.weight      | Block 29 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  270 | blk.29.ffn_down.weight    | Block 29 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  271 | blk.29.ffn_gate.weight    | Block 29 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  272 | blk.29.ffn_norm.weight    | Block 29 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  273 | blk.29.ffn_up.weight      | Block 29 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.29: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  274 | blk.30.attn_k.weight      | Block 30 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  275 | blk.30.attn_norm.weight   | Block 30 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  276 | blk.30.attn_output.weight | Block 30 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  277 | blk.30.attn_q.weight      | Block 30 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  278 | blk.30.attn_v.weight      | Block 30 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  279 | blk.30.ffn_down.weight    | Block 30 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  280 | blk.30.ffn_gate.weight    | Block 30 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  281 | blk.30.ffn_norm.weight    | Block 30 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  282 | blk.30.ffn_up.weight      | Block 30 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.30: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  283 | blk.31.attn_k.weight      | Block 31 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  284 | blk.31.attn_norm.weight   | Block 31 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  285 | blk.31.attn_output.weight | Block 31 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  286 | blk.31.attn_q.weight      | Block 31 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  287 | blk.31.attn_v.weight      | Block 31 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  288 | blk.31.ffn_down.weight    | Block 31 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  289 | blk.31.ffn_gate.weight    | Block 31 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  290 | blk.31.ffn_norm.weight    | Block 31 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  291 | blk.31.ffn_up.weight      | Block 31 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.31: (~218M) 218112000
+- Percentage of total elements: 2.72%

scores/Llama-Guard-3-8B-Q4_K_S.md ADDED Viewed

	@@ -0,0 +1,978 @@

+# Llama-Guard-3-8B-Q4_K_S.gguf - GGUF Internal File Dump
+- Endian: LITTLE endian
+## Key Value Metadata Store
+There are 39 key-value pairs in this file
+| POS | TYPE     |  Count | Key                                    | Value                                                               |
+|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
+|   1 | UINT32   |      1 | GGUF.version                           | 3                                                                   |
+|   2 | UINT64   |      1 | GGUF.tensor_count                      | 292                                                                 |
+|   3 | UINT64   |      1 | GGUF.kv_count                          | 36                                                                  |
+|   4 | STRING   |      1 | general.architecture                   | `llama`                                                             |
+|   5 | STRING   |      1 | general.type                           | `model`                                                             |
+|   6 | STRING   |      1 | general.name                           | `Llama Guard 3 8B`                                                  |
+|   7 | STRING   |      1 | general.basename                       | `Llama-Guard-3`                                                     |
+|   8 | STRING   |      1 | general.size_label                     | `8B`                                                                |
+|   9 | STRING   |      1 | general.license                        | `llama3.1`                                                          |
+|  10 | UINT32   |      1 | general.base_model.count               | 1                                                                   |
+|  11 | STRING   |      1 | general.base_model.0.name              | `Meta Llama 3.1 8B`                                                 |
+|  12 | STRING   |      1 | general.base_model.0.organization      | `Meta Llama`                                                        |
+|  13 | STRING   |      1 | general.base_model.0.repo_url          | `https://huggingface.co/meta-llama/Meta-Llama-3.1-8B`               |
+|  14 | [STRING] |      6 | general.tags                           | [ `facebook`, `meta`, `pytorch`, `llama`, `llama-3`, ... ]          |
+|  15 | [STRING] |      1 | general.languages                      | [ `en` ]                                                            |
+|  16 | UINT32   |      1 | llama.block_count                      | 32                                                                  |
+|  17 | UINT32   |      1 | llama.context_length                   | 131072                                                              |
+|  18 | UINT32   |      1 | llama.embedding_length                 | 4096                                                                |
+|  19 | UINT32   |      1 | llama.feed_forward_length              | 14336                                                               |
+|  20 | UINT32   |      1 | llama.attention.head_count             | 32                                                                  |
+|  21 | UINT32   |      1 | llama.attention.head_count_kv          | 8                                                                   |
+|  22 | FLOAT32  |      1 | llama.rope.freq_base                   | 500000.0                                                            |
+|  23 | FLOAT32  |      1 | llama.attention.layer_norm_rms_epsilon | 1e-05                                                               |
+|  24 | UINT32   |      1 | llama.vocab_size                       | 128256                                                              |
+|  25 | UINT32   |      1 | llama.rope.dimension_count             | 128                                                                 |
+|  26 | STRING   |      1 | tokenizer.ggml.model                   | `gpt2`                                                              |
+|  27 | STRING   |      1 | tokenizer.ggml.pre                     | `smaug-bpe`                                                         |
+|  28 | [STRING] | 128256 | tokenizer.ggml.tokens                  | [ `!`, `"`, `#`, `$`, `%`, ... ]                                    |
+|  29 | [INT32]  | 128256 | tokenizer.ggml.token_type              | [ 1, 1, 1, 1, 1, 1, 1, ... ]                                        |
+|  30 | [STRING] | 280147 | tokenizer.ggml.merges                  | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]                    |
+|  31 | UINT32   |      1 | tokenizer.ggml.bos_token_id            | 128000                                                              |
+|  32 | UINT32   |      1 | tokenizer.ggml.eos_token_id            | 128009                                                              |
+|  33 | STRING   |      1 | tokenizer.chat_template                | `{% if messages|length % 2 == 0`...`assistant<|end_header_id|>" }}` |
+|  34 | UINT32   |      1 | general.quantization_version           | 2                                                                   |
+|  35 | UINT32   |      1 | general.file_type                      | 14                                                                  |
+|  36 | STRING   |      1 | quantize.imatrix.file                  | `./imatrix/imatrix-Llama-Guard-3-8B-small.dat`                      |
+|  37 | STRING   |      1 | quantize.imatrix.dataset               | `../../datasets/imatrix/calibration_eur_small.txt`                  |
+|  38 | INT32    |      1 | quantize.imatrix.entries_count         | 224                                                                 |
+|  39 | INT32    |      1 | quantize.imatrix.chunks_count          | 962                                                                 |
+## Tensors Overview ~8B Elements
+Total number of elements in all tensors: 8030261312 Elements
+- [Llama-Guard-3-8B-Q4\_K\_S.gguf - GGUF Internal File Dump](#llama-guard-3-8b-q4_k_sgguf---gguf-internal-file-dump)
+  - [Key Value Metadata Store](#key-value-metadata-store)
+  - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
+    - [Tensor Data Offset](#tensor-data-offset)
+    - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
+    - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
+    - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
+    - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
+    - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
+    - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
+    - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
+    - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
+    - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
+    - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
+    - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
+    - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
+    - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
+    - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
+    - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
+    - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
+    - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
+    - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
+    - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
+    - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
+    - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
+    - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
+    - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
+    - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
+    - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
+    - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
+    - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
+    - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
+    - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
+    - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
+    - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
+    - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
+    - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
+### Tensor Data Offset
+This table contains the offset and data segment relative to start of file
+| T_ID | Tensor Layer Name         |  Data Offset (B) |    Data Size (B) |
+|-----:|:--------------------------|-----------------:|-----------------:|
+|    0 | output.weight             |         0x779880 |       0x119d0000 |
+|    1 | output_norm.weight        |       0x12149880 |           0x4000 |
+|    2 | rope_freqs.weight         |       0x1214d880 |            0x100 |
+|    3 | token_embd.weight         |       0x1214d980 |        0xd746000 |
+|    4 | blk.0.attn_k.weight       |       0x1f893980 |         0x1b8000 |
+|    5 | blk.0.attn_norm.weight    |       0x1fa4b980 |           0x4000 |
+|    6 | blk.0.attn_output.weight  |       0x1fa4f980 |         0x900000 |
+|    7 | blk.0.attn_q.weight       |       0x2034f980 |         0x6e0000 |
+|    8 | blk.0.attn_v.weight       |       0x20a2f980 |         0x240000 |
+|    9 | blk.0.ffn_down.weight     |       0x20c6f980 |        0x1f80000 |
+|   10 | blk.0.ffn_gate.weight     |       0x22bef980 |        0x1810000 |
+|   11 | blk.0.ffn_norm.weight     |       0x243ff980 |           0x4000 |
+|   12 | blk.0.ffn_up.weight       |       0x24403980 |        0x1810000 |
+|   13 | blk.1.attn_k.weight       |       0x25c13980 |         0x1b8000 |
+|   14 | blk.1.attn_norm.weight    |       0x25dcb980 |           0x4000 |
+|   15 | blk.1.attn_output.weight  |       0x25dcf980 |         0x900000 |
+|   16 | blk.1.attn_q.weight       |       0x266cf980 |         0x6e0000 |
+|   17 | blk.1.attn_v.weight       |       0x26daf980 |         0x240000 |
+|   18 | blk.1.ffn_down.weight     |       0x26fef980 |        0x2680000 |
+|   19 | blk.1.ffn_gate.weight     |       0x2966f980 |        0x1810000 |
+|   20 | blk.1.ffn_norm.weight     |       0x2ae7f980 |           0x4000 |
+|   21 | blk.1.ffn_up.weight       |       0x2ae83980 |        0x1810000 |
+|   22 | blk.2.attn_k.weight       |       0x2c693980 |         0x1b8000 |
+|   23 | blk.2.attn_norm.weight    |       0x2c84b980 |           0x4000 |
+|   24 | blk.2.attn_output.weight  |       0x2c84f980 |         0x900000 |
+|   25 | blk.2.attn_q.weight       |       0x2d14f980 |         0x6e0000 |
+|   26 | blk.2.attn_v.weight       |       0x2d82f980 |         0x240000 |
+|   27 | blk.2.ffn_down.weight     |       0x2da6f980 |        0x1f80000 |
+|   28 | blk.2.ffn_gate.weight     |       0x2f9ef980 |        0x1810000 |
+|   29 | blk.2.ffn_norm.weight     |       0x311ff980 |           0x4000 |
+|   30 | blk.2.ffn_up.weight       |       0x31203980 |        0x1810000 |
+|   31 | blk.3.attn_k.weight       |       0x32a13980 |         0x1b8000 |
+|   32 | blk.3.attn_norm.weight    |       0x32bcb980 |           0x4000 |
+|   33 | blk.3.attn_output.weight  |       0x32bcf980 |         0x900000 |
+|   34 | blk.3.attn_q.weight       |       0x334cf980 |         0x6e0000 |
+|   35 | blk.3.attn_v.weight       |       0x33baf980 |         0x240000 |
+|   36 | blk.3.ffn_down.weight     |       0x33def980 |        0x1f80000 |
+|   37 | blk.3.ffn_gate.weight     |       0x35d6f980 |        0x1810000 |
+|   38 | blk.3.ffn_norm.weight     |       0x3757f980 |           0x4000 |
+|   39 | blk.3.ffn_up.weight       |       0x37583980 |        0x1810000 |
+|   40 | blk.4.attn_k.weight       |       0x38d93980 |         0x1b8000 |
+|   41 | blk.4.attn_norm.weight    |       0x38f4b980 |           0x4000 |
+|   42 | blk.4.attn_output.weight  |       0x38f4f980 |         0x900000 |
+|   43 | blk.4.attn_q.weight       |       0x3984f980 |         0x6e0000 |
+|   44 | blk.4.attn_v.weight       |       0x39f2f980 |         0x240000 |
+|   45 | blk.4.ffn_down.weight     |       0x3a16f980 |        0x1f80000 |
+|   46 | blk.4.ffn_gate.weight     |       0x3c0ef980 |        0x1810000 |
+|   47 | blk.4.ffn_norm.weight     |       0x3d8ff980 |           0x4000 |
+|   48 | blk.4.ffn_up.weight       |       0x3d903980 |        0x1810000 |
+|   49 | blk.5.attn_k.weight       |       0x3f113980 |         0x1b8000 |
+|   50 | blk.5.attn_norm.weight    |       0x3f2cb980 |           0x4000 |
+|   51 | blk.5.attn_output.weight  |       0x3f2cf980 |         0x900000 |
+|   52 | blk.5.attn_q.weight       |       0x3fbcf980 |         0x6e0000 |
+|   53 | blk.5.attn_v.weight       |       0x402af980 |         0x240000 |
+|   54 | blk.5.ffn_down.weight     |       0x404ef980 |        0x1f80000 |
+|   55 | blk.5.ffn_gate.weight     |       0x4246f980 |        0x1810000 |
+|   56 | blk.5.ffn_norm.weight     |       0x43c7f980 |           0x4000 |
+|   57 | blk.5.ffn_up.weight       |       0x43c83980 |        0x1810000 |
+|   58 | blk.6.attn_k.weight       |       0x45493980 |         0x1b8000 |
+|   59 | blk.6.attn_norm.weight    |       0x4564b980 |           0x4000 |
+|   60 | blk.6.attn_output.weight  |       0x4564f980 |         0x900000 |
+|   61 | blk.6.attn_q.weight       |       0x45f4f980 |         0x6e0000 |
+|   62 | blk.6.attn_v.weight       |       0x4662f980 |         0x240000 |
+|   63 | blk.6.ffn_down.weight     |       0x4686f980 |        0x1f80000 |
+|   64 | blk.6.ffn_gate.weight     |       0x487ef980 |        0x1810000 |
+|   65 | blk.6.ffn_norm.weight     |       0x49fff980 |           0x4000 |
+|   66 | blk.6.ffn_up.weight       |       0x4a003980 |        0x1810000 |
+|   67 | blk.7.attn_k.weight       |       0x4b813980 |         0x1b8000 |
+|   68 | blk.7.attn_norm.weight    |       0x4b9cb980 |           0x4000 |
+|   69 | blk.7.attn_output.weight  |       0x4b9cf980 |         0x900000 |
+|   70 | blk.7.attn_q.weight       |       0x4c2cf980 |         0x6e0000 |
+|   71 | blk.7.attn_v.weight       |       0x4c9af980 |         0x240000 |
+|   72 | blk.7.ffn_down.weight     |       0x4cbef980 |        0x1f80000 |
+|   73 | blk.7.ffn_gate.weight     |       0x4eb6f980 |        0x1810000 |
+|   74 | blk.7.ffn_norm.weight     |       0x5037f980 |           0x4000 |
+|   75 | blk.7.ffn_up.weight       |       0x50383980 |        0x1810000 |
+|   76 | blk.8.attn_k.weight       |       0x51b93980 |         0x1b8000 |
+|   77 | blk.8.attn_norm.weight    |       0x51d4b980 |           0x4000 |
+|   78 | blk.8.attn_output.weight  |       0x51d4f980 |         0x900000 |
+|   79 | blk.8.attn_q.weight       |       0x5264f980 |         0x6e0000 |
+|   80 | blk.8.attn_v.weight       |       0x52d2f980 |         0x240000 |
+|   81 | blk.8.ffn_down.weight     |       0x52f6f980 |        0x1f80000 |
+|   82 | blk.8.ffn_gate.weight     |       0x54eef980 |        0x1810000 |
+|   83 | blk.8.ffn_norm.weight     |       0x566ff980 |           0x4000 |
+|   84 | blk.8.ffn_up.weight       |       0x56703980 |        0x1810000 |
+|   85 | blk.9.attn_k.weight       |       0x57f13980 |         0x1b8000 |
+|   86 | blk.9.attn_norm.weight    |       0x580cb980 |           0x4000 |
+|   87 | blk.9.attn_output.weight  |       0x580cf980 |         0x900000 |
+|   88 | blk.9.attn_q.weight       |       0x589cf980 |         0x6e0000 |
+|   89 | blk.9.attn_v.weight       |       0x590af980 |         0x240000 |
+|   90 | blk.9.ffn_down.weight     |       0x592ef980 |        0x1f80000 |
+|   91 | blk.9.ffn_gate.weight     |       0x5b26f980 |        0x1810000 |
+|   92 | blk.9.ffn_norm.weight     |       0x5ca7f980 |           0x4000 |
+|   93 | blk.9.ffn_up.weight       |       0x5ca83980 |        0x1810000 |
+|   94 | blk.10.attn_k.weight      |       0x5e293980 |         0x1b8000 |
+|   95 | blk.10.attn_norm.weight   |       0x5e44b980 |           0x4000 |
+|   96 | blk.10.attn_output.weight |       0x5e44f980 |         0x900000 |
+|   97 | blk.10.attn_q.weight      |       0x5ed4f980 |         0x6e0000 |
+|   98 | blk.10.attn_v.weight      |       0x5f42f980 |         0x240000 |
+|   99 | blk.10.ffn_down.weight    |       0x5f66f980 |        0x1f80000 |
+|  100 | blk.10.ffn_gate.weight    |       0x615ef980 |        0x1810000 |
+|  101 | blk.10.ffn_norm.weight    |       0x62dff980 |           0x4000 |
+|  102 | blk.10.ffn_up.weight      |       0x62e03980 |        0x1810000 |
+|  103 | blk.11.attn_k.weight      |       0x64613980 |         0x1b8000 |
+|  104 | blk.11.attn_norm.weight   |       0x647cb980 |           0x4000 |
+|  105 | blk.11.attn_output.weight |       0x647cf980 |         0x900000 |
+|  106 | blk.11.attn_q.weight      |       0x650cf980 |         0x6e0000 |
+|  107 | blk.11.attn_v.weight      |       0x657af980 |         0x240000 |
+|  108 | blk.11.ffn_down.weight    |       0x659ef980 |        0x1f80000 |
+|  109 | blk.11.ffn_gate.weight    |       0x6796f980 |        0x1810000 |
+|  110 | blk.11.ffn_norm.weight    |       0x6917f980 |           0x4000 |
+|  111 | blk.11.ffn_up.weight      |       0x69183980 |        0x1810000 |
+|  112 | blk.12.attn_k.weight      |       0x6a993980 |         0x1b8000 |
+|  113 | blk.12.attn_norm.weight   |       0x6ab4b980 |           0x4000 |
+|  114 | blk.12.attn_output.weight |       0x6ab4f980 |         0x900000 |
+|  115 | blk.12.attn_q.weight      |       0x6b44f980 |         0x6e0000 |
+|  116 | blk.12.attn_v.weight      |       0x6bb2f980 |         0x240000 |
+|  117 | blk.12.ffn_down.weight    |       0x6bd6f980 |        0x1f80000 |
+|  118 | blk.12.ffn_gate.weight    |       0x6dcef980 |        0x1810000 |
+|  119 | blk.12.ffn_norm.weight    |       0x6f4ff980 |           0x4000 |
+|  120 | blk.12.ffn_up.weight      |       0x6f503980 |        0x1810000 |
+|  121 | blk.13.attn_k.weight      |       0x70d13980 |         0x240000 |
+|  122 | blk.13.attn_norm.weight   |       0x70f53980 |           0x4000 |
+|  123 | blk.13.attn_output.weight |       0x70f57980 |         0x900000 |
+|  124 | blk.13.attn_q.weight      |       0x71857980 |         0x900000 |
+|  125 | blk.13.attn_v.weight      |       0x72157980 |         0x240000 |
+|  126 | blk.13.ffn_down.weight    |       0x72397980 |        0x1f80000 |
+|  127 | blk.13.ffn_gate.weight    |       0x74317980 |        0x1810000 |
+|  128 | blk.13.ffn_norm.weight    |       0x75b27980 |           0x4000 |
+|  129 | blk.13.ffn_up.weight      |       0x75b2b980 |        0x1810000 |
+|  130 | blk.14.attn_k.weight      |       0x7733b980 |         0x240000 |
+|  131 | blk.14.attn_norm.weight   |       0x7757b980 |           0x4000 |
+|  132 | blk.14.attn_output.weight |       0x7757f980 |         0x900000 |
+|  133 | blk.14.attn_q.weight      |       0x77e7f980 |         0x900000 |
+|  134 | blk.14.attn_v.weight      |       0x7877f980 |         0x240000 |
+|  135 | blk.14.ffn_down.weight    |       0x789bf980 |        0x1f80000 |
+|  136 | blk.14.ffn_gate.weight    |       0x7a93f980 |        0x1810000 |
+|  137 | blk.14.ffn_norm.weight    |       0x7c14f980 |           0x4000 |
+|  138 | blk.14.ffn_up.weight      |       0x7c153980 |        0x1810000 |
+|  139 | blk.15.attn_k.weight      |       0x7d963980 |         0x1b8000 |
+|  140 | blk.15.attn_norm.weight   |       0x7db1b980 |           0x4000 |
+|  141 | blk.15.attn_output.weight |       0x7db1f980 |         0x900000 |
+|  142 | blk.15.attn_q.weight      |       0x7e41f980 |         0x6e0000 |
+|  143 | blk.15.attn_v.weight      |       0x7eaff980 |         0x240000 |
+|  144 | blk.15.ffn_down.weight    |       0x7ed3f980 |        0x1f80000 |
+|  145 | blk.15.ffn_gate.weight    |       0x80cbf980 |        0x1810000 |
+|  146 | blk.15.ffn_norm.weight    |       0x824cf980 |           0x4000 |
+|  147 | blk.15.ffn_up.weight      |       0x824d3980 |        0x1810000 |
+|  148 | blk.16.attn_k.weight      |       0x83ce3980 |         0x240000 |
+|  149 | blk.16.attn_norm.weight   |       0x83f23980 |           0x4000 |
+|  150 | blk.16.attn_output.weight |       0x83f27980 |         0x900000 |
+|  151 | blk.16.attn_q.weight      |       0x84827980 |         0x900000 |
+|  152 | blk.16.attn_v.weight      |       0x85127980 |         0x240000 |
+|  153 | blk.16.ffn_down.weight    |       0x85367980 |        0x1f80000 |
+|  154 | blk.16.ffn_gate.weight    |       0x872e7980 |        0x1f80000 |
+|  155 | blk.16.ffn_norm.weight    |       0x89267980 |           0x4000 |
+|  156 | blk.16.ffn_up.weight      |       0x8926b980 |        0x1f80000 |
+|  157 | blk.17.attn_k.weight      |       0x8b1eb980 |         0x1b8000 |
+|  158 | blk.17.attn_norm.weight   |       0x8b3a3980 |           0x4000 |
+|  159 | blk.17.attn_output.weight |       0x8b3a7980 |         0x900000 |
+|  160 | blk.17.attn_q.weight      |       0x8bca7980 |         0x6e0000 |
+|  161 | blk.17.attn_v.weight      |       0x8c387980 |         0x240000 |
+|  162 | blk.17.ffn_down.weight    |       0x8c5c7980 |        0x2680000 |
+|  163 | blk.17.ffn_gate.weight    |       0x8ec47980 |        0x1f80000 |
+|  164 | blk.17.ffn_norm.weight    |       0x90bc7980 |           0x4000 |
+|  165 | blk.17.ffn_up.weight      |       0x90bcb980 |        0x1f80000 |
+|  166 | blk.18.attn_k.weight      |       0x92b4b980 |         0x240000 |
+|  167 | blk.18.attn_norm.weight   |       0x92d8b980 |           0x4000 |
+|  168 | blk.18.attn_output.weight |       0x92d8f980 |         0x900000 |
+|  169 | blk.18.attn_q.weight      |       0x9368f980 |         0x900000 |
+|  170 | blk.18.attn_v.weight      |       0x93f8f980 |         0x240000 |
+|  171 | blk.18.ffn_down.weight    |       0x941cf980 |        0x2680000 |
+|  172 | blk.18.ffn_gate.weight    |       0x9684f980 |        0x1f80000 |
+|  173 | blk.18.ffn_norm.weight    |       0x987cf980 |           0x4000 |
+|  174 | blk.18.ffn_up.weight      |       0x987d3980 |        0x1f80000 |
+|  175 | blk.19.attn_k.weight      |       0x9a753980 |         0x240000 |
+|  176 | blk.19.attn_norm.weight   |       0x9a993980 |           0x4000 |
+|  177 | blk.19.attn_output.weight |       0x9a997980 |         0x900000 |
+|  178 | blk.19.attn_q.weight      |       0x9b297980 |         0x900000 |
+|  179 | blk.19.attn_v.weight      |       0x9bb97980 |         0x240000 |
+|  180 | blk.19.ffn_down.weight    |       0x9bdd7980 |        0x2680000 |
+|  181 | blk.19.ffn_gate.weight    |       0x9e457980 |        0x1f80000 |
+|  182 | blk.19.ffn_norm.weight    |       0xa03d7980 |           0x4000 |
+|  183 | blk.19.ffn_up.weight      |       0xa03db980 |        0x1f80000 |
+|  184 | blk.20.attn_k.weight      |       0xa235b980 |         0x240000 |
+|  185 | blk.20.attn_norm.weight   |       0xa259b980 |           0x4000 |
+|  186 | blk.20.attn_output.weight |       0xa259f980 |         0x900000 |
+|  187 | blk.20.attn_q.weight      |       0xa2e9f980 |         0x900000 |
+|  188 | blk.20.attn_v.weight      |       0xa379f980 |         0x240000 |
+|  189 | blk.20.ffn_down.weight    |       0xa39df980 |        0x2680000 |
+|  190 | blk.20.ffn_gate.weight    |       0xa605f980 |        0x1f80000 |
+|  191 | blk.20.ffn_norm.weight    |       0xa7fdf980 |           0x4000 |
+|  192 | blk.20.ffn_up.weight      |       0xa7fe3980 |        0x1f80000 |
+|  193 | blk.21.attn_k.weight      |       0xa9f63980 |         0x240000 |
+|  194 | blk.21.attn_norm.weight   |       0xaa1a3980 |           0x4000 |
+|  195 | blk.21.attn_output.weight |       0xaa1a7980 |         0x900000 |
+|  196 | blk.21.attn_q.weight      |       0xaaaa7980 |         0x900000 |
+|  197 | blk.21.attn_v.weight      |       0xab3a7980 |         0x240000 |
+|  198 | blk.21.ffn_down.weight    |       0xab5e7980 |        0x2680000 |
+|  199 | blk.21.ffn_gate.weight    |       0xadc67980 |        0x1f80000 |
+|  200 | blk.21.ffn_norm.weight    |       0xafbe7980 |           0x4000 |
+|  201 | blk.21.ffn_up.weight      |       0xafbeb980 |        0x1f80000 |
+|  202 | blk.22.attn_k.weight      |       0xb1b6b980 |         0x240000 |
+|  203 | blk.22.attn_norm.weight   |       0xb1dab980 |           0x4000 |
+|  204 | blk.22.attn_output.weight |       0xb1daf980 |         0x900000 |
+|  205 | blk.22.attn_q.weight      |       0xb26af980 |         0x900000 |
+|  206 | blk.22.attn_v.weight      |       0xb2faf980 |         0x240000 |
+|  207 | blk.22.ffn_down.weight    |       0xb31ef980 |        0x2680000 |
+|  208 | blk.22.ffn_gate.weight    |       0xb586f980 |        0x1f80000 |
+|  209 | blk.22.ffn_norm.weight    |       0xb77ef980 |           0x4000 |
+|  210 | blk.22.ffn_up.weight      |       0xb77f3980 |        0x1f80000 |
+|  211 | blk.23.attn_k.weight      |       0xb9773980 |         0x240000 |
+|  212 | blk.23.attn_norm.weight   |       0xb99b3980 |           0x4000 |
+|  213 | blk.23.attn_output.weight |       0xb99b7980 |         0x900000 |
+|  214 | blk.23.attn_q.weight      |       0xba2b7980 |         0x900000 |
+|  215 | blk.23.attn_v.weight      |       0xbabb7980 |         0x240000 |
+|  216 | blk.23.ffn_down.weight    |       0xbadf7980 |        0x2680000 |
+|  217 | blk.23.ffn_gate.weight    |       0xbd477980 |        0x1f80000 |
+|  218 | blk.23.ffn_norm.weight    |       0xbf3f7980 |           0x4000 |
+|  219 | blk.23.ffn_up.weight      |       0xbf3fb980 |        0x1f80000 |
+|  220 | blk.24.attn_k.weight      |       0xc137b980 |         0x240000 |
+|  221 | blk.24.attn_norm.weight   |       0xc15bb980 |           0x4000 |
+|  222 | blk.24.attn_output.weight |       0xc15bf980 |         0x900000 |
+|  223 | blk.24.attn_q.weight      |       0xc1ebf980 |         0x900000 |
+|  224 | blk.24.attn_v.weight      |       0xc27bf980 |         0x240000 |
+|  225 | blk.24.ffn_down.weight    |       0xc29ff980 |        0x2680000 |
+|  226 | blk.24.ffn_gate.weight    |       0xc507f980 |        0x1f80000 |
+|  227 | blk.24.ffn_norm.weight    |       0xc6fff980 |           0x4000 |
+|  228 | blk.24.ffn_up.weight      |       0xc7003980 |        0x1f80000 |
+|  229 | blk.25.attn_k.weight      |       0xc8f83980 |         0x240000 |
+|  230 | blk.25.attn_norm.weight   |       0xc91c3980 |           0x4000 |
+|  231 | blk.25.attn_output.weight |       0xc91c7980 |         0x900000 |
+|  232 | blk.25.attn_q.weight      |       0xc9ac7980 |         0x900000 |
+|  233 | blk.25.attn_v.weight      |       0xca3c7980 |         0x240000 |
+|  234 | blk.25.ffn_down.weight    |       0xca607980 |        0x2680000 |
+|  235 | blk.25.ffn_gate.weight    |       0xccc87980 |        0x1f80000 |
+|  236 | blk.25.ffn_norm.weight    |       0xcec07980 |           0x4000 |
+|  237 | blk.25.ffn_up.weight      |       0xcec0b980 |        0x1f80000 |
+|  238 | blk.26.attn_k.weight      |       0xd0b8b980 |         0x240000 |
+|  239 | blk.26.attn_norm.weight   |       0xd0dcb980 |           0x4000 |
+|  240 | blk.26.attn_output.weight |       0xd0dcf980 |         0x900000 |
+|  241 | blk.26.attn_q.weight      |       0xd16cf980 |         0x900000 |
+|  242 | blk.26.attn_v.weight      |       0xd1fcf980 |         0x240000 |
+|  243 | blk.26.ffn_down.weight    |       0xd220f980 |        0x2680000 |
+|  244 | blk.26.ffn_gate.weight    |       0xd488f980 |        0x1f80000 |
+|  245 | blk.26.ffn_norm.weight    |       0xd680f980 |           0x4000 |
+|  246 | blk.26.ffn_up.weight      |       0xd6813980 |        0x1f80000 |
+|  247 | blk.27.attn_k.weight      |       0xd8793980 |         0x240000 |
+|  248 | blk.27.attn_norm.weight   |       0xd89d3980 |           0x4000 |
+|  249 | blk.27.attn_output.weight |       0xd89d7980 |         0x900000 |
+|  250 | blk.27.attn_q.weight      |       0xd92d7980 |         0x900000 |
+|  251 | blk.27.attn_v.weight      |       0xd9bd7980 |         0x240000 |
+|  252 | blk.27.ffn_down.weight    |       0xd9e17980 |        0x2680000 |
+|  253 | blk.27.ffn_gate.weight    |       0xdc497980 |        0x1f80000 |
+|  254 | blk.27.ffn_norm.weight    |       0xde417980 |           0x4000 |
+|  255 | blk.27.ffn_up.weight      |       0xde41b980 |        0x1f80000 |
+|  256 | blk.28.attn_k.weight      |       0xe039b980 |         0x240000 |
+|  257 | blk.28.attn_norm.weight   |       0xe05db980 |           0x4000 |
+|  258 | blk.28.attn_output.weight |       0xe05df980 |         0x900000 |
+|  259 | blk.28.attn_q.weight      |       0xe0edf980 |         0x900000 |
+|  260 | blk.28.attn_v.weight      |       0xe17df980 |         0x240000 |
+|  261 | blk.28.ffn_down.weight    |       0xe1a1f980 |        0x2680000 |
+|  262 | blk.28.ffn_gate.weight    |       0xe409f980 |        0x1f80000 |
+|  263 | blk.28.ffn_norm.weight    |       0xe601f980 |           0x4000 |
+|  264 | blk.28.ffn_up.weight      |       0xe6023980 |        0x1f80000 |
+|  265 | blk.29.attn_k.weight      |       0xe7fa3980 |         0x240000 |
+|  266 | blk.29.attn_norm.weight   |       0xe81e3980 |           0x4000 |
+|  267 | blk.29.attn_output.weight |       0xe81e7980 |         0x900000 |
+|  268 | blk.29.attn_q.weight      |       0xe8ae7980 |         0x900000 |
+|  269 | blk.29.attn_v.weight      |       0xe93e7980 |         0x240000 |
+|  270 | blk.29.ffn_down.weight    |       0xe9627980 |        0x2680000 |
+|  271 | blk.29.ffn_gate.weight    |       0xebca7980 |        0x1f80000 |
+|  272 | blk.29.ffn_norm.weight    |       0xedc27980 |           0x4000 |
+|  273 | blk.29.ffn_up.weight      |       0xedc2b980 |        0x1f80000 |
+|  274 | blk.30.attn_k.weight      |       0xefbab980 |         0x240000 |
+|  275 | blk.30.attn_norm.weight   |       0xefdeb980 |           0x4000 |
+|  276 | blk.30.attn_output.weight |       0xefdef980 |         0x900000 |
+|  277 | blk.30.attn_q.weight      |       0xf06ef980 |         0x900000 |
+|  278 | blk.30.attn_v.weight      |       0xf0fef980 |         0x240000 |
+|  279 | blk.30.ffn_down.weight    |       0xf122f980 |        0x2680000 |
+|  280 | blk.30.ffn_gate.weight    |       0xf38af980 |        0x1f80000 |
+|  281 | blk.30.ffn_norm.weight    |       0xf582f980 |           0x4000 |
+|  282 | blk.30.ffn_up.weight      |       0xf5833980 |        0x1f80000 |
+|  283 | blk.31.attn_k.weight      |       0xf77b3980 |         0x1b8000 |
+|  284 | blk.31.attn_norm.weight   |       0xf796b980 |           0x4000 |
+|  285 | blk.31.attn_output.weight |       0xf796f980 |         0x900000 |
+|  286 | blk.31.attn_q.weight      |       0xf826f980 |         0x6e0000 |
+|  287 | blk.31.attn_v.weight      |       0xf894f980 |         0x240000 |
+|  288 | blk.31.ffn_down.weight    |       0xf8b8f980 |        0x2680000 |
+|  289 | blk.31.ffn_gate.weight    |       0xfb20f980 |        0x1f80000 |
+|  290 | blk.31.ffn_norm.weight    |       0xfd18f980 |           0x4000 |
+|  291 | blk.31.ffn_up.weight      |       0xfd193980 |        0x1f80000 |
+### <a name="base">Base Tensor Group : ~1B Elements</a>
+| T_ID | Tensor Layer Name  | Human Friendly Tensor Layer Name | Elements          | Shape                 | Type |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
+|    0 | output.weight      | Output (W)                       | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q4_K |
+|    1 | output_norm.weight | Output Normalization (W)         | (  ~4K)      4096 | 4096 x      1 x 1 x 1 | F32  |
+|    2 | rope_freqs.weight  | Rope_Freqs (W)                   | (   64)        64 |   64 x      1 x 1 x 1 | F32  |
+|    3 | token_embd.weight  | Token Embedding (W)              | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q3_K |
+- Total elements in base: ( ~1B) 1050677312
+- Percentage of total elements: 13.08%
+### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|    4 | blk.0.attn_k.weight      | Block 0 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|    5 | blk.0.attn_norm.weight   | Block 0 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|    6 | blk.0.attn_output.weight | Block 0 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|    7 | blk.0.attn_q.weight      | Block 0 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|    8 | blk.0.attn_v.weight      | Block 0 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|    9 | blk.0.ffn_down.weight    | Block 0 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   10 | blk.0.ffn_gate.weight    | Block 0 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   11 | blk.0.ffn_norm.weight    | Block 0 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   12 | blk.0.ffn_up.weight      | Block 0 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.0: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   13 | blk.1.attn_k.weight      | Block 1 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   14 | blk.1.attn_norm.weight   | Block 1 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   15 | blk.1.attn_output.weight | Block 1 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   16 | blk.1.attn_q.weight      | Block 1 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   17 | blk.1.attn_v.weight      | Block 1 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   18 | blk.1.ffn_down.weight    | Block 1 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   19 | blk.1.ffn_gate.weight    | Block 1 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   20 | blk.1.ffn_norm.weight    | Block 1 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   21 | blk.1.ffn_up.weight      | Block 1 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.1: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   22 | blk.2.attn_k.weight      | Block 2 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   23 | blk.2.attn_norm.weight   | Block 2 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   24 | blk.2.attn_output.weight | Block 2 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   25 | blk.2.attn_q.weight      | Block 2 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   26 | blk.2.attn_v.weight      | Block 2 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   27 | blk.2.ffn_down.weight    | Block 2 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   28 | blk.2.ffn_gate.weight    | Block 2 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   29 | blk.2.ffn_norm.weight    | Block 2 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   30 | blk.2.ffn_up.weight      | Block 2 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.2: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   31 | blk.3.attn_k.weight      | Block 3 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   32 | blk.3.attn_norm.weight   | Block 3 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   33 | blk.3.attn_output.weight | Block 3 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   34 | blk.3.attn_q.weight      | Block 3 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   35 | blk.3.attn_v.weight      | Block 3 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   36 | blk.3.ffn_down.weight    | Block 3 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   37 | blk.3.ffn_gate.weight    | Block 3 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   38 | blk.3.ffn_norm.weight    | Block 3 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   39 | blk.3.ffn_up.weight      | Block 3 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.3: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   40 | blk.4.attn_k.weight      | Block 4 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   41 | blk.4.attn_norm.weight   | Block 4 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   42 | blk.4.attn_output.weight | Block 4 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   43 | blk.4.attn_q.weight      | Block 4 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   44 | blk.4.attn_v.weight      | Block 4 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   45 | blk.4.ffn_down.weight    | Block 4 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   46 | blk.4.ffn_gate.weight    | Block 4 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   47 | blk.4.ffn_norm.weight    | Block 4 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   48 | blk.4.ffn_up.weight      | Block 4 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.4: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   49 | blk.5.attn_k.weight      | Block 5 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   50 | blk.5.attn_norm.weight   | Block 5 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   51 | blk.5.attn_output.weight | Block 5 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   52 | blk.5.attn_q.weight      | Block 5 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   53 | blk.5.attn_v.weight      | Block 5 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   54 | blk.5.ffn_down.weight    | Block 5 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   55 | blk.5.ffn_gate.weight    | Block 5 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   56 | blk.5.ffn_norm.weight    | Block 5 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   57 | blk.5.ffn_up.weight      | Block 5 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.5: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   58 | blk.6.attn_k.weight      | Block 6 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   59 | blk.6.attn_norm.weight   | Block 6 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   60 | blk.6.attn_output.weight | Block 6 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   61 | blk.6.attn_q.weight      | Block 6 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   62 | blk.6.attn_v.weight      | Block 6 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   63 | blk.6.ffn_down.weight    | Block 6 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   64 | blk.6.ffn_gate.weight    | Block 6 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   65 | blk.6.ffn_norm.weight    | Block 6 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   66 | blk.6.ffn_up.weight      | Block 6 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.6: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   67 | blk.7.attn_k.weight      | Block 7 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   68 | blk.7.attn_norm.weight   | Block 7 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   69 | blk.7.attn_output.weight | Block 7 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   70 | blk.7.attn_q.weight      | Block 7 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   71 | blk.7.attn_v.weight      | Block 7 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   72 | blk.7.ffn_down.weight    | Block 7 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   73 | blk.7.ffn_gate.weight    | Block 7 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   74 | blk.7.ffn_norm.weight    | Block 7 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   75 | blk.7.ffn_up.weight      | Block 7 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.7: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   76 | blk.8.attn_k.weight      | Block 8 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   77 | blk.8.attn_norm.weight   | Block 8 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   78 | blk.8.attn_output.weight | Block 8 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   79 | blk.8.attn_q.weight      | Block 8 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   80 | blk.8.attn_v.weight      | Block 8 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   81 | blk.8.ffn_down.weight    | Block 8 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   82 | blk.8.ffn_gate.weight    | Block 8 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   83 | blk.8.ffn_norm.weight    | Block 8 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   84 | blk.8.ffn_up.weight      | Block 8 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.8: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   85 | blk.9.attn_k.weight      | Block 9 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   86 | blk.9.attn_norm.weight   | Block 9 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   87 | blk.9.attn_output.weight | Block 9 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   88 | blk.9.attn_q.weight      | Block 9 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   89 | blk.9.attn_v.weight      | Block 9 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   90 | blk.9.ffn_down.weight    | Block 9 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|   91 | blk.9.ffn_gate.weight    | Block 9 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|   92 | blk.9.ffn_norm.weight    | Block 9 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   93 | blk.9.ffn_up.weight      | Block 9 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.9: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|   94 | blk.10.attn_k.weight      | Block 10 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|   95 | blk.10.attn_norm.weight   | Block 10 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   96 | blk.10.attn_output.weight | Block 10 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   97 | blk.10.attn_q.weight      | Block 10 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|   98 | blk.10.attn_v.weight      | Block 10 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   99 | blk.10.ffn_down.weight    | Block 10 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  100 | blk.10.ffn_gate.weight    | Block 10 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  101 | blk.10.ffn_norm.weight    | Block 10 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  102 | blk.10.ffn_up.weight      | Block 10 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.10: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  103 | blk.11.attn_k.weight      | Block 11 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  104 | blk.11.attn_norm.weight   | Block 11 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  105 | blk.11.attn_output.weight | Block 11 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  106 | blk.11.attn_q.weight      | Block 11 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  107 | blk.11.attn_v.weight      | Block 11 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  108 | blk.11.ffn_down.weight    | Block 11 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  109 | blk.11.ffn_gate.weight    | Block 11 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  110 | blk.11.ffn_norm.weight    | Block 11 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  111 | blk.11.ffn_up.weight      | Block 11 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.11: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  112 | blk.12.attn_k.weight      | Block 12 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  113 | blk.12.attn_norm.weight   | Block 12 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  114 | blk.12.attn_output.weight | Block 12 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  115 | blk.12.attn_q.weight      | Block 12 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  116 | blk.12.attn_v.weight      | Block 12 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  117 | blk.12.ffn_down.weight    | Block 12 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  118 | blk.12.ffn_gate.weight    | Block 12 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  119 | blk.12.ffn_norm.weight    | Block 12 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  120 | blk.12.ffn_up.weight      | Block 12 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.12: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  121 | blk.13.attn_k.weight      | Block 13 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  122 | blk.13.attn_norm.weight   | Block 13 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  123 | blk.13.attn_output.weight | Block 13 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  124 | blk.13.attn_q.weight      | Block 13 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  125 | blk.13.attn_v.weight      | Block 13 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  126 | blk.13.ffn_down.weight    | Block 13 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  127 | blk.13.ffn_gate.weight    | Block 13 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  128 | blk.13.ffn_norm.weight    | Block 13 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  129 | blk.13.ffn_up.weight      | Block 13 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.13: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  130 | blk.14.attn_k.weight      | Block 14 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  131 | blk.14.attn_norm.weight   | Block 14 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  132 | blk.14.attn_output.weight | Block 14 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  133 | blk.14.attn_q.weight      | Block 14 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  134 | blk.14.attn_v.weight      | Block 14 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  135 | blk.14.ffn_down.weight    | Block 14 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  136 | blk.14.ffn_gate.weight    | Block 14 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  137 | blk.14.ffn_norm.weight    | Block 14 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  138 | blk.14.ffn_up.weight      | Block 14 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.14: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  139 | blk.15.attn_k.weight      | Block 15 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  140 | blk.15.attn_norm.weight   | Block 15 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  141 | blk.15.attn_output.weight | Block 15 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  142 | blk.15.attn_q.weight      | Block 15 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  143 | blk.15.attn_v.weight      | Block 15 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  144 | blk.15.ffn_down.weight    | Block 15 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  145 | blk.15.ffn_gate.weight    | Block 15 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+|  146 | blk.15.ffn_norm.weight    | Block 15 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  147 | blk.15.ffn_up.weight      | Block 15 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q3_K |
+- Total elements in blk.15: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  148 | blk.16.attn_k.weight      | Block 16 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  149 | blk.16.attn_norm.weight   | Block 16 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  150 | blk.16.attn_output.weight | Block 16 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  151 | blk.16.attn_q.weight      | Block 16 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  152 | blk.16.attn_v.weight      | Block 16 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  153 | blk.16.ffn_down.weight    | Block 16 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q4_K |
+|  154 | blk.16.ffn_gate.weight    | Block 16 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  155 | blk.16.ffn_norm.weight    | Block 16 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  156 | blk.16.ffn_up.weight      | Block 16 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.16: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  157 | blk.17.attn_k.weight      | Block 17 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  158 | blk.17.attn_norm.weight   | Block 17 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  159 | blk.17.attn_output.weight | Block 17 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  160 | blk.17.attn_q.weight      | Block 17 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  161 | blk.17.attn_v.weight      | Block 17 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  162 | blk.17.ffn_down.weight    | Block 17 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  163 | blk.17.ffn_gate.weight    | Block 17 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  164 | blk.17.ffn_norm.weight    | Block 17 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  165 | blk.17.ffn_up.weight      | Block 17 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.17: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  166 | blk.18.attn_k.weight      | Block 18 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  167 | blk.18.attn_norm.weight   | Block 18 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  168 | blk.18.attn_output.weight | Block 18 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  169 | blk.18.attn_q.weight      | Block 18 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  170 | blk.18.attn_v.weight      | Block 18 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  171 | blk.18.ffn_down.weight    | Block 18 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  172 | blk.18.ffn_gate.weight    | Block 18 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  173 | blk.18.ffn_norm.weight    | Block 18 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  174 | blk.18.ffn_up.weight      | Block 18 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.18: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  175 | blk.19.attn_k.weight      | Block 19 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  176 | blk.19.attn_norm.weight   | Block 19 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  177 | blk.19.attn_output.weight | Block 19 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  178 | blk.19.attn_q.weight      | Block 19 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  179 | blk.19.attn_v.weight      | Block 19 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  180 | blk.19.ffn_down.weight    | Block 19 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  181 | blk.19.ffn_gate.weight    | Block 19 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  182 | blk.19.ffn_norm.weight    | Block 19 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  183 | blk.19.ffn_up.weight      | Block 19 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.19: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  184 | blk.20.attn_k.weight      | Block 20 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  185 | blk.20.attn_norm.weight   | Block 20 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  186 | blk.20.attn_output.weight | Block 20 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  187 | blk.20.attn_q.weight      | Block 20 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  188 | blk.20.attn_v.weight      | Block 20 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  189 | blk.20.ffn_down.weight    | Block 20 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  190 | blk.20.ffn_gate.weight    | Block 20 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  191 | blk.20.ffn_norm.weight    | Block 20 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  192 | blk.20.ffn_up.weight      | Block 20 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.20: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  193 | blk.21.attn_k.weight      | Block 21 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  194 | blk.21.attn_norm.weight   | Block 21 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  195 | blk.21.attn_output.weight | Block 21 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  196 | blk.21.attn_q.weight      | Block 21 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  197 | blk.21.attn_v.weight      | Block 21 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  198 | blk.21.ffn_down.weight    | Block 21 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  199 | blk.21.ffn_gate.weight    | Block 21 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  200 | blk.21.ffn_norm.weight    | Block 21 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  201 | blk.21.ffn_up.weight      | Block 21 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.21: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  202 | blk.22.attn_k.weight      | Block 22 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  203 | blk.22.attn_norm.weight   | Block 22 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  204 | blk.22.attn_output.weight | Block 22 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  205 | blk.22.attn_q.weight      | Block 22 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  206 | blk.22.attn_v.weight      | Block 22 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  207 | blk.22.ffn_down.weight    | Block 22 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  208 | blk.22.ffn_gate.weight    | Block 22 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  209 | blk.22.ffn_norm.weight    | Block 22 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  210 | blk.22.ffn_up.weight      | Block 22 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.22: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  211 | blk.23.attn_k.weight      | Block 23 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  212 | blk.23.attn_norm.weight   | Block 23 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  213 | blk.23.attn_output.weight | Block 23 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  214 | blk.23.attn_q.weight      | Block 23 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  215 | blk.23.attn_v.weight      | Block 23 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  216 | blk.23.ffn_down.weight    | Block 23 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  217 | blk.23.ffn_gate.weight    | Block 23 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  218 | blk.23.ffn_norm.weight    | Block 23 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  219 | blk.23.ffn_up.weight      | Block 23 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.23: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  220 | blk.24.attn_k.weight      | Block 24 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  221 | blk.24.attn_norm.weight   | Block 24 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  222 | blk.24.attn_output.weight | Block 24 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  223 | blk.24.attn_q.weight      | Block 24 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  224 | blk.24.attn_v.weight      | Block 24 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  225 | blk.24.ffn_down.weight    | Block 24 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  226 | blk.24.ffn_gate.weight    | Block 24 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  227 | blk.24.ffn_norm.weight    | Block 24 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  228 | blk.24.ffn_up.weight      | Block 24 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.24: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  229 | blk.25.attn_k.weight      | Block 25 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  230 | blk.25.attn_norm.weight   | Block 25 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  231 | blk.25.attn_output.weight | Block 25 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  232 | blk.25.attn_q.weight      | Block 25 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  233 | blk.25.attn_v.weight      | Block 25 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  234 | blk.25.ffn_down.weight    | Block 25 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  235 | blk.25.ffn_gate.weight    | Block 25 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  236 | blk.25.ffn_norm.weight    | Block 25 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  237 | blk.25.ffn_up.weight      | Block 25 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.25: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  238 | blk.26.attn_k.weight      | Block 26 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  239 | blk.26.attn_norm.weight   | Block 26 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  240 | blk.26.attn_output.weight | Block 26 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  241 | blk.26.attn_q.weight      | Block 26 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  242 | blk.26.attn_v.weight      | Block 26 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  243 | blk.26.ffn_down.weight    | Block 26 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  244 | blk.26.ffn_gate.weight    | Block 26 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  245 | blk.26.ffn_norm.weight    | Block 26 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  246 | blk.26.ffn_up.weight      | Block 26 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.26: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  247 | blk.27.attn_k.weight      | Block 27 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  248 | blk.27.attn_norm.weight   | Block 27 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  249 | blk.27.attn_output.weight | Block 27 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  250 | blk.27.attn_q.weight      | Block 27 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  251 | blk.27.attn_v.weight      | Block 27 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  252 | blk.27.ffn_down.weight    | Block 27 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  253 | blk.27.ffn_gate.weight    | Block 27 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  254 | blk.27.ffn_norm.weight    | Block 27 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  255 | blk.27.ffn_up.weight      | Block 27 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.27: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  256 | blk.28.attn_k.weight      | Block 28 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  257 | blk.28.attn_norm.weight   | Block 28 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  258 | blk.28.attn_output.weight | Block 28 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  259 | blk.28.attn_q.weight      | Block 28 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  260 | blk.28.attn_v.weight      | Block 28 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  261 | blk.28.ffn_down.weight    | Block 28 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  262 | blk.28.ffn_gate.weight    | Block 28 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  263 | blk.28.ffn_norm.weight    | Block 28 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  264 | blk.28.ffn_up.weight      | Block 28 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.28: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  265 | blk.29.attn_k.weight      | Block 29 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  266 | blk.29.attn_norm.weight   | Block 29 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  267 | blk.29.attn_output.weight | Block 29 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  268 | blk.29.attn_q.weight      | Block 29 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  269 | blk.29.attn_v.weight      | Block 29 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  270 | blk.29.ffn_down.weight    | Block 29 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  271 | blk.29.ffn_gate.weight    | Block 29 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  272 | blk.29.ffn_norm.weight    | Block 29 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  273 | blk.29.ffn_up.weight      | Block 29 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.29: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  274 | blk.30.attn_k.weight      | Block 30 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  275 | blk.30.attn_norm.weight   | Block 30 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  276 | blk.30.attn_output.weight | Block 30 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  277 | blk.30.attn_q.weight      | Block 30 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  278 | blk.30.attn_v.weight      | Block 30 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  279 | blk.30.ffn_down.weight    | Block 30 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  280 | blk.30.ffn_gate.weight    | Block 30 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  281 | blk.30.ffn_norm.weight    | Block 30 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  282 | blk.30.ffn_up.weight      | Block 30 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.30: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  283 | blk.31.attn_k.weight      | Block 31 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q3_K |
+|  284 | blk.31.attn_norm.weight   | Block 31 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  285 | blk.31.attn_output.weight | Block 31 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  286 | blk.31.attn_q.weight      | Block 31 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q3_K |
+|  287 | blk.31.attn_v.weight      | Block 31 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  288 | blk.31.ffn_down.weight    | Block 31 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  289 | blk.31.ffn_gate.weight    | Block 31 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  290 | blk.31.ffn_norm.weight    | Block 31 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  291 | blk.31.ffn_up.weight      | Block 31 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.31: (~218M) 218112000
+- Percentage of total elements: 2.72%

scores/Llama-Guard-3-8B-Q5_K_M.md ADDED Viewed

	@@ -0,0 +1,978 @@

+# Llama-Guard-3-8B-Q5_K_M.gguf - GGUF Internal File Dump
+- Endian: LITTLE endian
+## Key Value Metadata Store
+There are 39 key-value pairs in this file
+| POS | TYPE     |  Count | Key                                    | Value                                                               |
+|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
+|   1 | UINT32   |      1 | GGUF.version                           | 3                                                                   |
+|   2 | UINT64   |      1 | GGUF.tensor_count                      | 292                                                                 |
+|   3 | UINT64   |      1 | GGUF.kv_count                          | 36                                                                  |
+|   4 | STRING   |      1 | general.architecture                   | `llama`                                                             |
+|   5 | STRING   |      1 | general.type                           | `model`                                                             |
+|   6 | STRING   |      1 | general.name                           | `Llama Guard 3 8B`                                                  |
+|   7 | STRING   |      1 | general.basename                       | `Llama-Guard-3`                                                     |
+|   8 | STRING   |      1 | general.size_label                     | `8B`                                                                |
+|   9 | STRING   |      1 | general.license                        | `llama3.1`                                                          |
+|  10 | UINT32   |      1 | general.base_model.count               | 1                                                                   |
+|  11 | STRING   |      1 | general.base_model.0.name              | `Meta Llama 3.1 8B`                                                 |
+|  12 | STRING   |      1 | general.base_model.0.organization      | `Meta Llama`                                                        |
+|  13 | STRING   |      1 | general.base_model.0.repo_url          | `https://huggingface.co/meta-llama/Meta-Llama-3.1-8B`               |
+|  14 | [STRING] |      6 | general.tags                           | [ `facebook`, `meta`, `pytorch`, `llama`, `llama-3`, ... ]          |
+|  15 | [STRING] |      1 | general.languages                      | [ `en` ]                                                            |
+|  16 | UINT32   |      1 | llama.block_count                      | 32                                                                  |
+|  17 | UINT32   |      1 | llama.context_length                   | 131072                                                              |
+|  18 | UINT32   |      1 | llama.embedding_length                 | 4096                                                                |
+|  19 | UINT32   |      1 | llama.feed_forward_length              | 14336                                                               |
+|  20 | UINT32   |      1 | llama.attention.head_count             | 32                                                                  |
+|  21 | UINT32   |      1 | llama.attention.head_count_kv          | 8                                                                   |
+|  22 | FLOAT32  |      1 | llama.rope.freq_base                   | 500000.0                                                            |
+|  23 | FLOAT32  |      1 | llama.attention.layer_norm_rms_epsilon | 1e-05                                                               |
+|  24 | UINT32   |      1 | llama.vocab_size                       | 128256                                                              |
+|  25 | UINT32   |      1 | llama.rope.dimension_count             | 128                                                                 |
+|  26 | STRING   |      1 | tokenizer.ggml.model                   | `gpt2`                                                              |
+|  27 | STRING   |      1 | tokenizer.ggml.pre                     | `smaug-bpe`                                                         |
+|  28 | [STRING] | 128256 | tokenizer.ggml.tokens                  | [ `!`, `"`, `#`, `$`, `%`, ... ]                                    |
+|  29 | [INT32]  | 128256 | tokenizer.ggml.token_type              | [ 1, 1, 1, 1, 1, 1, 1, ... ]                                        |
+|  30 | [STRING] | 280147 | tokenizer.ggml.merges                  | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]                    |
+|  31 | UINT32   |      1 | tokenizer.ggml.bos_token_id            | 128000                                                              |
+|  32 | UINT32   |      1 | tokenizer.ggml.eos_token_id            | 128009                                                              |
+|  33 | STRING   |      1 | tokenizer.chat_template                | `{% if messages|length % 2 == 0`...`assistant<|end_header_id|>" }}` |
+|  34 | UINT32   |      1 | general.quantization_version           | 2                                                                   |
+|  35 | UINT32   |      1 | general.file_type                      | 17                                                                  |
+|  36 | STRING   |      1 | quantize.imatrix.file                  | `./imatrix/imatrix-Llama-Guard-3-8B-small.dat`                      |
+|  37 | STRING   |      1 | quantize.imatrix.dataset               | `../../datasets/imatrix/calibration_eur_small.txt`                  |
+|  38 | INT32    |      1 | quantize.imatrix.entries_count         | 224                                                                 |
+|  39 | INT32    |      1 | quantize.imatrix.chunks_count          | 962                                                                 |
+## Tensors Overview ~8B Elements
+Total number of elements in all tensors: 8030261312 Elements
+- [Llama-Guard-3-8B-Q5\_K\_M.gguf - GGUF Internal File Dump](#llama-guard-3-8b-q5_k_mgguf---gguf-internal-file-dump)
+  - [Key Value Metadata Store](#key-value-metadata-store)
+  - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
+    - [Tensor Data Offset](#tensor-data-offset)
+    - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
+    - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
+    - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
+    - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
+    - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
+    - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
+    - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
+    - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
+    - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
+    - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
+    - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
+    - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
+    - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
+    - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
+    - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
+    - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
+    - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
+    - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
+    - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
+    - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
+    - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
+    - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
+    - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
+    - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
+    - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
+    - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
+    - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
+    - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
+    - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
+    - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
+    - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
+    - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
+    - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
+### Tensor Data Offset
+This table contains the offset and data segment relative to start of file
+| T_ID | Tensor Layer Name         |  Data Offset (B) |    Data Size (B) |
+|-----:|:--------------------------|-----------------:|-----------------:|
+|    0 | output.weight             |         0x779880 |       0x15870000 |
+|    1 | output_norm.weight        |       0x15fe9880 |           0x4000 |
+|    2 | rope_freqs.weight         |       0x15fed880 |            0x100 |
+|    3 | token_embd.weight         |       0x15fed980 |        0xd746000 |
+|    4 | blk.0.attn_k.weight       |       0x23733980 |         0x240000 |
+|    5 | blk.0.attn_norm.weight    |       0x23973980 |           0x4000 |
+|    6 | blk.0.attn_output.weight  |       0x23977980 |         0xb00000 |
+|    7 | blk.0.attn_q.weight       |       0x24477980 |         0x900000 |
+|    8 | blk.0.attn_v.weight       |       0x24d77980 |         0x2c0000 |
+|    9 | blk.0.ffn_down.weight     |       0x25037980 |        0x2df0000 |
+|   10 | blk.0.ffn_gate.weight     |       0x27e27980 |        0x1f80000 |
+|   11 | blk.0.ffn_norm.weight     |       0x29da7980 |           0x4000 |
+|   12 | blk.0.ffn_up.weight       |       0x29dab980 |        0x1f80000 |
+|   13 | blk.1.attn_k.weight       |       0x2bd2b980 |         0x240000 |
+|   14 | blk.1.attn_norm.weight    |       0x2bf6b980 |           0x4000 |
+|   15 | blk.1.attn_output.weight  |       0x2bf6f980 |         0xb00000 |
+|   16 | blk.1.attn_q.weight       |       0x2ca6f980 |         0x900000 |
+|   17 | blk.1.attn_v.weight       |       0x2d36f980 |         0x2c0000 |
+|   18 | blk.1.ffn_down.weight     |       0x2d62f980 |        0x2df0000 |
+|   19 | blk.1.ffn_gate.weight     |       0x3041f980 |        0x1f80000 |
+|   20 | blk.1.ffn_norm.weight     |       0x3239f980 |           0x4000 |
+|   21 | blk.1.ffn_up.weight       |       0x323a3980 |        0x1f80000 |
+|   22 | blk.2.attn_k.weight       |       0x34323980 |         0x240000 |
+|   23 | blk.2.attn_norm.weight    |       0x34563980 |           0x4000 |
+|   24 | blk.2.attn_output.weight  |       0x34567980 |         0xb00000 |
+|   25 | blk.2.attn_q.weight       |       0x35067980 |         0x900000 |
+|   26 | blk.2.attn_v.weight       |       0x35967980 |         0x2c0000 |
+|   27 | blk.2.ffn_down.weight     |       0x35c27980 |        0x2df0000 |
+|   28 | blk.2.ffn_gate.weight     |       0x38a17980 |        0x1f80000 |
+|   29 | blk.2.ffn_norm.weight     |       0x3a997980 |           0x4000 |
+|   30 | blk.2.ffn_up.weight       |       0x3a99b980 |        0x1f80000 |
+|   31 | blk.3.attn_k.weight       |       0x3c91b980 |         0x240000 |
+|   32 | blk.3.attn_norm.weight    |       0x3cb5b980 |           0x4000 |
+|   33 | blk.3.attn_output.weight  |       0x3cb5f980 |         0xb00000 |
+|   34 | blk.3.attn_q.weight       |       0x3d65f980 |         0x900000 |
+|   35 | blk.3.attn_v.weight       |       0x3df5f980 |         0x2c0000 |
+|   36 | blk.3.ffn_down.weight     |       0x3e21f980 |        0x2df0000 |
+|   37 | blk.3.ffn_gate.weight     |       0x4100f980 |        0x1f80000 |
+|   38 | blk.3.ffn_norm.weight     |       0x42f8f980 |           0x4000 |
+|   39 | blk.3.ffn_up.weight       |       0x42f93980 |        0x1f80000 |
+|   40 | blk.4.attn_k.weight       |       0x44f13980 |         0x240000 |
+|   41 | blk.4.attn_norm.weight    |       0x45153980 |           0x4000 |
+|   42 | blk.4.attn_output.weight  |       0x45157980 |         0xb00000 |
+|   43 | blk.4.attn_q.weight       |       0x45c57980 |         0x900000 |
+|   44 | blk.4.attn_v.weight       |       0x46557980 |         0x2c0000 |
+|   45 | blk.4.ffn_down.weight     |       0x46817980 |        0x2df0000 |
+|   46 | blk.4.ffn_gate.weight     |       0x49607980 |        0x1f80000 |
+|   47 | blk.4.ffn_norm.weight     |       0x4b587980 |           0x4000 |
+|   48 | blk.4.ffn_up.weight       |       0x4b58b980 |        0x1f80000 |
+|   49 | blk.5.attn_k.weight       |       0x4d50b980 |         0x240000 |
+|   50 | blk.5.attn_norm.weight    |       0x4d74b980 |           0x4000 |
+|   51 | blk.5.attn_output.weight  |       0x4d74f980 |         0xb00000 |
+|   52 | blk.5.attn_q.weight       |       0x4e24f980 |         0x900000 |
+|   53 | blk.5.attn_v.weight       |       0x4eb4f980 |         0x2c0000 |
+|   54 | blk.5.ffn_down.weight     |       0x4ee0f980 |        0x2df0000 |
+|   55 | blk.5.ffn_gate.weight     |       0x51bff980 |        0x1f80000 |
+|   56 | blk.5.ffn_norm.weight     |       0x53b7f980 |           0x4000 |
+|   57 | blk.5.ffn_up.weight       |       0x53b83980 |        0x1f80000 |
+|   58 | blk.6.attn_k.weight       |       0x55b03980 |         0x240000 |
+|   59 | blk.6.attn_norm.weight    |       0x55d43980 |           0x4000 |
+|   60 | blk.6.attn_output.weight  |       0x55d47980 |         0xb00000 |
+|   61 | blk.6.attn_q.weight       |       0x56847980 |         0x900000 |
+|   62 | blk.6.attn_v.weight       |       0x57147980 |         0x2c0000 |
+|   63 | blk.6.ffn_down.weight     |       0x57407980 |        0x2df0000 |
+|   64 | blk.6.ffn_gate.weight     |       0x5a1f7980 |        0x1f80000 |
+|   65 | blk.6.ffn_norm.weight     |       0x5c177980 |           0x4000 |
+|   66 | blk.6.ffn_up.weight       |       0x5c17b980 |        0x1f80000 |
+|   67 | blk.7.attn_k.weight       |       0x5e0fb980 |         0x240000 |
+|   68 | blk.7.attn_norm.weight    |       0x5e33b980 |           0x4000 |
+|   69 | blk.7.attn_output.weight  |       0x5e33f980 |         0xb00000 |
+|   70 | blk.7.attn_q.weight       |       0x5ee3f980 |         0x900000 |
+|   71 | blk.7.attn_v.weight       |       0x5f73f980 |         0x2c0000 |
+|   72 | blk.7.ffn_down.weight     |       0x5f9ff980 |        0x2df0000 |
+|   73 | blk.7.ffn_gate.weight     |       0x627ef980 |        0x1f80000 |
+|   74 | blk.7.ffn_norm.weight     |       0x6476f980 |           0x4000 |
+|   75 | blk.7.ffn_up.weight       |       0x64773980 |        0x1f80000 |
+|   76 | blk.8.attn_k.weight       |       0x666f3980 |         0x240000 |
+|   77 | blk.8.attn_norm.weight    |       0x66933980 |           0x4000 |
+|   78 | blk.8.attn_output.weight  |       0x66937980 |         0xb00000 |
+|   79 | blk.8.attn_q.weight       |       0x67437980 |         0x900000 |
+|   80 | blk.8.attn_v.weight       |       0x67d37980 |         0x2c0000 |
+|   81 | blk.8.ffn_down.weight     |       0x67ff7980 |        0x2df0000 |
+|   82 | blk.8.ffn_gate.weight     |       0x6ade7980 |        0x1f80000 |
+|   83 | blk.8.ffn_norm.weight     |       0x6cd67980 |           0x4000 |
+|   84 | blk.8.ffn_up.weight       |       0x6cd6b980 |        0x1f80000 |
+|   85 | blk.9.attn_k.weight       |       0x6eceb980 |         0x240000 |
+|   86 | blk.9.attn_norm.weight    |       0x6ef2b980 |           0x4000 |
+|   87 | blk.9.attn_output.weight  |       0x6ef2f980 |         0xb00000 |
+|   88 | blk.9.attn_q.weight       |       0x6fa2f980 |         0x900000 |
+|   89 | blk.9.attn_v.weight       |       0x7032f980 |         0x2c0000 |
+|   90 | blk.9.ffn_down.weight     |       0x705ef980 |        0x2df0000 |
+|   91 | blk.9.ffn_gate.weight     |       0x733df980 |        0x1f80000 |
+|   92 | blk.9.ffn_norm.weight     |       0x7535f980 |           0x4000 |
+|   93 | blk.9.ffn_up.weight       |       0x75363980 |        0x1f80000 |
+|   94 | blk.10.attn_k.weight      |       0x772e3980 |         0x240000 |
+|   95 | blk.10.attn_norm.weight   |       0x77523980 |           0x4000 |
+|   96 | blk.10.attn_output.weight |       0x77527980 |         0xb00000 |
+|   97 | blk.10.attn_q.weight      |       0x78027980 |         0x900000 |
+|   98 | blk.10.attn_v.weight      |       0x78927980 |         0x2c0000 |
+|   99 | blk.10.ffn_down.weight    |       0x78be7980 |        0x2df0000 |
+|  100 | blk.10.ffn_gate.weight    |       0x7b9d7980 |        0x1f80000 |
+|  101 | blk.10.ffn_norm.weight    |       0x7d957980 |           0x4000 |
+|  102 | blk.10.ffn_up.weight      |       0x7d95b980 |        0x1f80000 |
+|  103 | blk.11.attn_k.weight      |       0x7f8db980 |         0x240000 |
+|  104 | blk.11.attn_norm.weight   |       0x7fb1b980 |           0x4000 |
+|  105 | blk.11.attn_output.weight |       0x7fb1f980 |         0xb00000 |
+|  106 | blk.11.attn_q.weight      |       0x8061f980 |         0x900000 |
+|  107 | blk.11.attn_v.weight      |       0x80f1f980 |         0x2c0000 |
+|  108 | blk.11.ffn_down.weight    |       0x811df980 |        0x2df0000 |
+|  109 | blk.11.ffn_gate.weight    |       0x83fcf980 |        0x1f80000 |
+|  110 | blk.11.ffn_norm.weight    |       0x85f4f980 |           0x4000 |
+|  111 | blk.11.ffn_up.weight      |       0x85f53980 |        0x1f80000 |
+|  112 | blk.12.attn_k.weight      |       0x87ed3980 |         0x240000 |
+|  113 | blk.12.attn_norm.weight   |       0x88113980 |           0x4000 |
+|  114 | blk.12.attn_output.weight |       0x88117980 |         0xb00000 |
+|  115 | blk.12.attn_q.weight      |       0x88c17980 |         0x900000 |
+|  116 | blk.12.attn_v.weight      |       0x89517980 |         0x2c0000 |
+|  117 | blk.12.ffn_down.weight    |       0x897d7980 |        0x2df0000 |
+|  118 | blk.12.ffn_gate.weight    |       0x8c5c7980 |        0x1f80000 |
+|  119 | blk.12.ffn_norm.weight    |       0x8e547980 |           0x4000 |
+|  120 | blk.12.ffn_up.weight      |       0x8e54b980 |        0x1f80000 |
+|  121 | blk.13.attn_k.weight      |       0x904cb980 |         0x2c0000 |
+|  122 | blk.13.attn_norm.weight   |       0x9078b980 |           0x4000 |
+|  123 | blk.13.attn_output.weight |       0x9078f980 |         0xb00000 |
+|  124 | blk.13.attn_q.weight      |       0x9128f980 |         0xb00000 |
+|  125 | blk.13.attn_v.weight      |       0x91d8f980 |         0x348000 |
+|  126 | blk.13.ffn_down.weight    |       0x920d7980 |        0x2df0000 |
+|  127 | blk.13.ffn_gate.weight    |       0x94ec7980 |        0x1f80000 |
+|  128 | blk.13.ffn_norm.weight    |       0x96e47980 |           0x4000 |
+|  129 | blk.13.ffn_up.weight      |       0x96e4b980 |        0x1f80000 |
+|  130 | blk.14.attn_k.weight      |       0x98dcb980 |         0x2c0000 |
+|  131 | blk.14.attn_norm.weight   |       0x9908b980 |           0x4000 |
+|  132 | blk.14.attn_output.weight |       0x9908f980 |         0xb00000 |
+|  133 | blk.14.attn_q.weight      |       0x99b8f980 |         0xb00000 |
+|  134 | blk.14.attn_v.weight      |       0x9a68f980 |         0x348000 |
+|  135 | blk.14.ffn_down.weight    |       0x9a9d7980 |        0x2df0000 |
+|  136 | blk.14.ffn_gate.weight    |       0x9d7c7980 |        0x1f80000 |
+|  137 | blk.14.ffn_norm.weight    |       0x9f747980 |           0x4000 |
+|  138 | blk.14.ffn_up.weight      |       0x9f74b980 |        0x1f80000 |
+|  139 | blk.15.attn_k.weight      |       0xa16cb980 |         0x240000 |
+|  140 | blk.15.attn_norm.weight   |       0xa190b980 |           0x4000 |
+|  141 | blk.15.attn_output.weight |       0xa190f980 |         0xb00000 |
+|  142 | blk.15.attn_q.weight      |       0xa240f980 |         0x900000 |
+|  143 | blk.15.attn_v.weight      |       0xa2d0f980 |         0x2c0000 |
+|  144 | blk.15.ffn_down.weight    |       0xa2fcf980 |        0x2df0000 |
+|  145 | blk.15.ffn_gate.weight    |       0xa5dbf980 |        0x1f80000 |
+|  146 | blk.15.ffn_norm.weight    |       0xa7d3f980 |           0x4000 |
+|  147 | blk.15.ffn_up.weight      |       0xa7d43980 |        0x1f80000 |
+|  148 | blk.16.attn_k.weight      |       0xa9cc3980 |         0x2c0000 |
+|  149 | blk.16.attn_norm.weight   |       0xa9f83980 |           0x4000 |
+|  150 | blk.16.attn_output.weight |       0xa9f87980 |         0xb00000 |
+|  151 | blk.16.attn_q.weight      |       0xaaa87980 |         0xb00000 |
+|  152 | blk.16.attn_v.weight      |       0xab587980 |         0x348000 |
+|  153 | blk.16.ffn_down.weight    |       0xab8cf980 |        0x2df0000 |
+|  154 | blk.16.ffn_gate.weight    |       0xae6bf980 |        0x2680000 |
+|  155 | blk.16.ffn_norm.weight    |       0xb0d3f980 |           0x4000 |
+|  156 | blk.16.ffn_up.weight      |       0xb0d43980 |        0x2680000 |
+|  157 | blk.17.attn_k.weight      |       0xb33c3980 |         0x240000 |
+|  158 | blk.17.attn_norm.weight   |       0xb3603980 |           0x4000 |
+|  159 | blk.17.attn_output.weight |       0xb3607980 |         0xb00000 |
+|  160 | blk.17.attn_q.weight      |       0xb4107980 |         0x900000 |
+|  161 | blk.17.attn_v.weight      |       0xb4a07980 |         0x2c0000 |
+|  162 | blk.17.ffn_down.weight    |       0xb4cc7980 |        0x2df0000 |
+|  163 | blk.17.ffn_gate.weight    |       0xb7ab7980 |        0x2680000 |
+|  164 | blk.17.ffn_norm.weight    |       0xba137980 |           0x4000 |
+|  165 | blk.17.ffn_up.weight      |       0xba13b980 |        0x2680000 |
+|  166 | blk.18.attn_k.weight      |       0xbc7bb980 |         0x2c0000 |
+|  167 | blk.18.attn_norm.weight   |       0xbca7b980 |           0x4000 |
+|  168 | blk.18.attn_output.weight |       0xbca7f980 |         0xb00000 |
+|  169 | blk.18.attn_q.weight      |       0xbd57f980 |         0xb00000 |
+|  170 | blk.18.attn_v.weight      |       0xbe07f980 |         0x348000 |
+|  171 | blk.18.ffn_down.weight    |       0xbe3c7980 |        0x2df0000 |
+|  172 | blk.18.ffn_gate.weight    |       0xc11b7980 |        0x2680000 |
+|  173 | blk.18.ffn_norm.weight    |       0xc3837980 |           0x4000 |
+|  174 | blk.18.ffn_up.weight      |       0xc383b980 |        0x2680000 |
+|  175 | blk.19.attn_k.weight      |       0xc5ebb980 |         0x2c0000 |
+|  176 | blk.19.attn_norm.weight   |       0xc617b980 |           0x4000 |
+|  177 | blk.19.attn_output.weight |       0xc617f980 |         0xb00000 |
+|  178 | blk.19.attn_q.weight      |       0xc6c7f980 |         0xb00000 |
+|  179 | blk.19.attn_v.weight      |       0xc777f980 |         0x348000 |
+|  180 | blk.19.ffn_down.weight    |       0xc7ac7980 |        0x2df0000 |
+|  181 | blk.19.ffn_gate.weight    |       0xca8b7980 |        0x2680000 |
+|  182 | blk.19.ffn_norm.weight    |       0xccf37980 |           0x4000 |
+|  183 | blk.19.ffn_up.weight      |       0xccf3b980 |        0x2680000 |
+|  184 | blk.20.attn_k.weight      |       0xcf5bb980 |         0x2c0000 |
+|  185 | blk.20.attn_norm.weight   |       0xcf87b980 |           0x4000 |
+|  186 | blk.20.attn_output.weight |       0xcf87f980 |         0xb00000 |
+|  187 | blk.20.attn_q.weight      |       0xd037f980 |         0xb00000 |
+|  188 | blk.20.attn_v.weight      |       0xd0e7f980 |         0x348000 |
+|  189 | blk.20.ffn_down.weight    |       0xd11c7980 |        0x2df0000 |
+|  190 | blk.20.ffn_gate.weight    |       0xd3fb7980 |        0x2680000 |
+|  191 | blk.20.ffn_norm.weight    |       0xd6637980 |           0x4000 |
+|  192 | blk.20.ffn_up.weight      |       0xd663b980 |        0x2680000 |
+|  193 | blk.21.attn_k.weight      |       0xd8cbb980 |         0x2c0000 |
+|  194 | blk.21.attn_norm.weight   |       0xd8f7b980 |           0x4000 |
+|  195 | blk.21.attn_output.weight |       0xd8f7f980 |         0xb00000 |
+|  196 | blk.21.attn_q.weight      |       0xd9a7f980 |         0xb00000 |
+|  197 | blk.21.attn_v.weight      |       0xda57f980 |         0x348000 |
+|  198 | blk.21.ffn_down.weight    |       0xda8c7980 |        0x2df0000 |
+|  199 | blk.21.ffn_gate.weight    |       0xdd6b7980 |        0x2680000 |
+|  200 | blk.21.ffn_norm.weight    |       0xdfd37980 |           0x4000 |
+|  201 | blk.21.ffn_up.weight      |       0xdfd3b980 |        0x2680000 |
+|  202 | blk.22.attn_k.weight      |       0xe23bb980 |         0x2c0000 |
+|  203 | blk.22.attn_norm.weight   |       0xe267b980 |           0x4000 |
+|  204 | blk.22.attn_output.weight |       0xe267f980 |         0xb00000 |
+|  205 | blk.22.attn_q.weight      |       0xe317f980 |         0xb00000 |
+|  206 | blk.22.attn_v.weight      |       0xe3c7f980 |         0x348000 |
+|  207 | blk.22.ffn_down.weight    |       0xe3fc7980 |        0x2df0000 |
+|  208 | blk.22.ffn_gate.weight    |       0xe6db7980 |        0x2680000 |
+|  209 | blk.22.ffn_norm.weight    |       0xe9437980 |           0x4000 |
+|  210 | blk.22.ffn_up.weight      |       0xe943b980 |        0x2680000 |
+|  211 | blk.23.attn_k.weight      |       0xebabb980 |         0x2c0000 |
+|  212 | blk.23.attn_norm.weight   |       0xebd7b980 |           0x4000 |
+|  213 | blk.23.attn_output.weight |       0xebd7f980 |         0xb00000 |
+|  214 | blk.23.attn_q.weight      |       0xec87f980 |         0xb00000 |
+|  215 | blk.23.attn_v.weight      |       0xed37f980 |         0x348000 |
+|  216 | blk.23.ffn_down.weight    |       0xed6c7980 |        0x2df0000 |
+|  217 | blk.23.ffn_gate.weight    |       0xf04b7980 |        0x2680000 |
+|  218 | blk.23.ffn_norm.weight    |       0xf2b37980 |           0x4000 |
+|  219 | blk.23.ffn_up.weight      |       0xf2b3b980 |        0x2680000 |
+|  220 | blk.24.attn_k.weight      |       0xf51bb980 |         0x2c0000 |
+|  221 | blk.24.attn_norm.weight   |       0xf547b980 |           0x4000 |
+|  222 | blk.24.attn_output.weight |       0xf547f980 |         0xb00000 |
+|  223 | blk.24.attn_q.weight      |       0xf5f7f980 |         0xb00000 |
+|  224 | blk.24.attn_v.weight      |       0xf6a7f980 |         0x348000 |
+|  225 | blk.24.ffn_down.weight    |       0xf6dc7980 |        0x2df0000 |
+|  226 | blk.24.ffn_gate.weight    |       0xf9bb7980 |        0x2680000 |
+|  227 | blk.24.ffn_norm.weight    |       0xfc237980 |           0x4000 |
+|  228 | blk.24.ffn_up.weight      |       0xfc23b980 |        0x2680000 |
+|  229 | blk.25.attn_k.weight      |       0xfe8bb980 |         0x2c0000 |
+|  230 | blk.25.attn_norm.weight   |       0xfeb7b980 |           0x4000 |
+|  231 | blk.25.attn_output.weight |       0xfeb7f980 |         0xb00000 |
+|  232 | blk.25.attn_q.weight      |       0xff67f980 |         0xb00000 |
+|  233 | blk.25.attn_v.weight      |      0x10017f980 |         0x348000 |
+|  234 | blk.25.ffn_down.weight    |      0x1004c7980 |        0x2df0000 |
+|  235 | blk.25.ffn_gate.weight    |      0x1032b7980 |        0x2680000 |
+|  236 | blk.25.ffn_norm.weight    |      0x105937980 |           0x4000 |
+|  237 | blk.25.ffn_up.weight      |      0x10593b980 |        0x2680000 |
+|  238 | blk.26.attn_k.weight      |      0x107fbb980 |         0x2c0000 |
+|  239 | blk.26.attn_norm.weight   |      0x10827b980 |           0x4000 |
+|  240 | blk.26.attn_output.weight |      0x10827f980 |         0xb00000 |
+|  241 | blk.26.attn_q.weight      |      0x108d7f980 |         0xb00000 |
+|  242 | blk.26.attn_v.weight      |      0x10987f980 |         0x348000 |
+|  243 | blk.26.ffn_down.weight    |      0x109bc7980 |        0x2df0000 |
+|  244 | blk.26.ffn_gate.weight    |      0x10c9b7980 |        0x2680000 |
+|  245 | blk.26.ffn_norm.weight    |      0x10f037980 |           0x4000 |
+|  246 | blk.26.ffn_up.weight      |      0x10f03b980 |        0x2680000 |
+|  247 | blk.27.attn_k.weight      |      0x1116bb980 |         0x2c0000 |
+|  248 | blk.27.attn_norm.weight   |      0x11197b980 |           0x4000 |
+|  249 | blk.27.attn_output.weight |      0x11197f980 |         0xb00000 |
+|  250 | blk.27.attn_q.weight      |      0x11247f980 |         0xb00000 |
+|  251 | blk.27.attn_v.weight      |      0x112f7f980 |         0x348000 |
+|  252 | blk.27.ffn_down.weight    |      0x1132c7980 |        0x2df0000 |
+|  253 | blk.27.ffn_gate.weight    |      0x1160b7980 |        0x2680000 |
+|  254 | blk.27.ffn_norm.weight    |      0x118737980 |           0x4000 |
+|  255 | blk.27.ffn_up.weight      |      0x11873b980 |        0x2680000 |
+|  256 | blk.28.attn_k.weight      |      0x11adbb980 |         0x2c0000 |
+|  257 | blk.28.attn_norm.weight   |      0x11b07b980 |           0x4000 |
+|  258 | blk.28.attn_output.weight |      0x11b07f980 |         0xb00000 |
+|  259 | blk.28.attn_q.weight      |      0x11bb7f980 |         0xb00000 |
+|  260 | blk.28.attn_v.weight      |      0x11c67f980 |         0x348000 |
+|  261 | blk.28.ffn_down.weight    |      0x11c9c7980 |        0x2df0000 |
+|  262 | blk.28.ffn_gate.weight    |      0x11f7b7980 |        0x2680000 |
+|  263 | blk.28.ffn_norm.weight    |      0x121e37980 |           0x4000 |
+|  264 | blk.28.ffn_up.weight      |      0x121e3b980 |        0x2680000 |
+|  265 | blk.29.attn_k.weight      |      0x1244bb980 |         0x2c0000 |
+|  266 | blk.29.attn_norm.weight   |      0x12477b980 |           0x4000 |
+|  267 | blk.29.attn_output.weight |      0x12477f980 |         0xb00000 |
+|  268 | blk.29.attn_q.weight      |      0x12527f980 |         0xb00000 |
+|  269 | blk.29.attn_v.weight      |      0x125d7f980 |         0x348000 |
+|  270 | blk.29.ffn_down.weight    |      0x1260c7980 |        0x2df0000 |
+|  271 | blk.29.ffn_gate.weight    |      0x128eb7980 |        0x2680000 |
+|  272 | blk.29.ffn_norm.weight    |      0x12b537980 |           0x4000 |
+|  273 | blk.29.ffn_up.weight      |      0x12b53b980 |        0x2680000 |
+|  274 | blk.30.attn_k.weight      |      0x12dbbb980 |         0x2c0000 |
+|  275 | blk.30.attn_norm.weight   |      0x12de7b980 |           0x4000 |
+|  276 | blk.30.attn_output.weight |      0x12de7f980 |         0xb00000 |
+|  277 | blk.30.attn_q.weight      |      0x12e97f980 |         0xb00000 |
+|  278 | blk.30.attn_v.weight      |      0x12f47f980 |         0x348000 |
+|  279 | blk.30.ffn_down.weight    |      0x12f7c7980 |        0x2df0000 |
+|  280 | blk.30.ffn_gate.weight    |      0x1325b7980 |        0x2680000 |
+|  281 | blk.30.ffn_norm.weight    |      0x134c37980 |           0x4000 |
+|  282 | blk.30.ffn_up.weight      |      0x134c3b980 |        0x2680000 |
+|  283 | blk.31.attn_k.weight      |      0x1372bb980 |         0x240000 |
+|  284 | blk.31.attn_norm.weight   |      0x1374fb980 |           0x4000 |
+|  285 | blk.31.attn_output.weight |      0x1374ff980 |         0xb00000 |
+|  286 | blk.31.attn_q.weight      |      0x137fff980 |         0x900000 |
+|  287 | blk.31.attn_v.weight      |      0x1388ff980 |         0x2c0000 |
+|  288 | blk.31.ffn_down.weight    |      0x138bbf980 |        0x2df0000 |
+|  289 | blk.31.ffn_gate.weight    |      0x13b9af980 |        0x2680000 |
+|  290 | blk.31.ffn_norm.weight    |      0x13e02f980 |           0x4000 |
+|  291 | blk.31.ffn_up.weight      |      0x13e033980 |        0x2680000 |
+### <a name="base">Base Tensor Group : ~1B Elements</a>
+| T_ID | Tensor Layer Name  | Human Friendly Tensor Layer Name | Elements          | Shape                 | Type |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
+|    0 | output.weight      | Output (W)                       | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q5_K |
+|    1 | output_norm.weight | Output Normalization (W)         | (  ~4K)      4096 | 4096 x      1 x 1 x 1 | F32  |
+|    2 | rope_freqs.weight  | Rope_Freqs (W)                   | (   64)        64 |   64 x      1 x 1 x 1 | F32  |
+|    3 | token_embd.weight  | Token Embedding (W)              | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q3_K |
+- Total elements in base: ( ~1B) 1050677312
+- Percentage of total elements: 13.08%
+### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|    4 | blk.0.attn_k.weight      | Block 0 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|    5 | blk.0.attn_norm.weight   | Block 0 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|    6 | blk.0.attn_output.weight | Block 0 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|    7 | blk.0.attn_q.weight      | Block 0 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|    8 | blk.0.attn_v.weight      | Block 0 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|    9 | blk.0.ffn_down.weight    | Block 0 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|   10 | blk.0.ffn_gate.weight    | Block 0 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   11 | blk.0.ffn_norm.weight    | Block 0 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   12 | blk.0.ffn_up.weight      | Block 0 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.0: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   13 | blk.1.attn_k.weight      | Block 1 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   14 | blk.1.attn_norm.weight   | Block 1 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   15 | blk.1.attn_output.weight | Block 1 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   16 | blk.1.attn_q.weight      | Block 1 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   17 | blk.1.attn_v.weight      | Block 1 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   18 | blk.1.ffn_down.weight    | Block 1 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|   19 | blk.1.ffn_gate.weight    | Block 1 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   20 | blk.1.ffn_norm.weight    | Block 1 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   21 | blk.1.ffn_up.weight      | Block 1 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.1: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   22 | blk.2.attn_k.weight      | Block 2 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   23 | blk.2.attn_norm.weight   | Block 2 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   24 | blk.2.attn_output.weight | Block 2 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   25 | blk.2.attn_q.weight      | Block 2 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   26 | blk.2.attn_v.weight      | Block 2 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   27 | blk.2.ffn_down.weight    | Block 2 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|   28 | blk.2.ffn_gate.weight    | Block 2 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   29 | blk.2.ffn_norm.weight    | Block 2 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   30 | blk.2.ffn_up.weight      | Block 2 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.2: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   31 | blk.3.attn_k.weight      | Block 3 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   32 | blk.3.attn_norm.weight   | Block 3 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   33 | blk.3.attn_output.weight | Block 3 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   34 | blk.3.attn_q.weight      | Block 3 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   35 | blk.3.attn_v.weight      | Block 3 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   36 | blk.3.ffn_down.weight    | Block 3 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|   37 | blk.3.ffn_gate.weight    | Block 3 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   38 | blk.3.ffn_norm.weight    | Block 3 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   39 | blk.3.ffn_up.weight      | Block 3 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.3: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   40 | blk.4.attn_k.weight      | Block 4 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   41 | blk.4.attn_norm.weight   | Block 4 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   42 | blk.4.attn_output.weight | Block 4 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   43 | blk.4.attn_q.weight      | Block 4 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   44 | blk.4.attn_v.weight      | Block 4 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   45 | blk.4.ffn_down.weight    | Block 4 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|   46 | blk.4.ffn_gate.weight    | Block 4 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   47 | blk.4.ffn_norm.weight    | Block 4 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   48 | blk.4.ffn_up.weight      | Block 4 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.4: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   49 | blk.5.attn_k.weight      | Block 5 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   50 | blk.5.attn_norm.weight   | Block 5 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   51 | blk.5.attn_output.weight | Block 5 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   52 | blk.5.attn_q.weight      | Block 5 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   53 | blk.5.attn_v.weight      | Block 5 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   54 | blk.5.ffn_down.weight    | Block 5 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|   55 | blk.5.ffn_gate.weight    | Block 5 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   56 | blk.5.ffn_norm.weight    | Block 5 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   57 | blk.5.ffn_up.weight      | Block 5 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.5: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   58 | blk.6.attn_k.weight      | Block 6 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   59 | blk.6.attn_norm.weight   | Block 6 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   60 | blk.6.attn_output.weight | Block 6 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   61 | blk.6.attn_q.weight      | Block 6 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   62 | blk.6.attn_v.weight      | Block 6 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   63 | blk.6.ffn_down.weight    | Block 6 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|   64 | blk.6.ffn_gate.weight    | Block 6 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   65 | blk.6.ffn_norm.weight    | Block 6 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   66 | blk.6.ffn_up.weight      | Block 6 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.6: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   67 | blk.7.attn_k.weight      | Block 7 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   68 | blk.7.attn_norm.weight   | Block 7 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   69 | blk.7.attn_output.weight | Block 7 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   70 | blk.7.attn_q.weight      | Block 7 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   71 | blk.7.attn_v.weight      | Block 7 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   72 | blk.7.ffn_down.weight    | Block 7 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|   73 | blk.7.ffn_gate.weight    | Block 7 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   74 | blk.7.ffn_norm.weight    | Block 7 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   75 | blk.7.ffn_up.weight      | Block 7 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.7: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   76 | blk.8.attn_k.weight      | Block 8 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   77 | blk.8.attn_norm.weight   | Block 8 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   78 | blk.8.attn_output.weight | Block 8 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   79 | blk.8.attn_q.weight      | Block 8 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   80 | blk.8.attn_v.weight      | Block 8 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   81 | blk.8.ffn_down.weight    | Block 8 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|   82 | blk.8.ffn_gate.weight    | Block 8 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   83 | blk.8.ffn_norm.weight    | Block 8 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   84 | blk.8.ffn_up.weight      | Block 8 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.8: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   85 | blk.9.attn_k.weight      | Block 9 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   86 | blk.9.attn_norm.weight   | Block 9 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   87 | blk.9.attn_output.weight | Block 9 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   88 | blk.9.attn_q.weight      | Block 9 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   89 | blk.9.attn_v.weight      | Block 9 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   90 | blk.9.ffn_down.weight    | Block 9 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|   91 | blk.9.ffn_gate.weight    | Block 9 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   92 | blk.9.ffn_norm.weight    | Block 9 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   93 | blk.9.ffn_up.weight      | Block 9 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.9: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|   94 | blk.10.attn_k.weight      | Block 10 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   95 | blk.10.attn_norm.weight   | Block 10 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   96 | blk.10.attn_output.weight | Block 10 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   97 | blk.10.attn_q.weight      | Block 10 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   98 | blk.10.attn_v.weight      | Block 10 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   99 | blk.10.ffn_down.weight    | Block 10 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  100 | blk.10.ffn_gate.weight    | Block 10 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  101 | blk.10.ffn_norm.weight    | Block 10 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  102 | blk.10.ffn_up.weight      | Block 10 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.10: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  103 | blk.11.attn_k.weight      | Block 11 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  104 | blk.11.attn_norm.weight   | Block 11 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  105 | blk.11.attn_output.weight | Block 11 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  106 | blk.11.attn_q.weight      | Block 11 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  107 | blk.11.attn_v.weight      | Block 11 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  108 | blk.11.ffn_down.weight    | Block 11 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  109 | blk.11.ffn_gate.weight    | Block 11 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  110 | blk.11.ffn_norm.weight    | Block 11 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  111 | blk.11.ffn_up.weight      | Block 11 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.11: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  112 | blk.12.attn_k.weight      | Block 12 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  113 | blk.12.attn_norm.weight   | Block 12 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  114 | blk.12.attn_output.weight | Block 12 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  115 | blk.12.attn_q.weight      | Block 12 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  116 | blk.12.attn_v.weight      | Block 12 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  117 | blk.12.ffn_down.weight    | Block 12 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  118 | blk.12.ffn_gate.weight    | Block 12 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  119 | blk.12.ffn_norm.weight    | Block 12 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  120 | blk.12.ffn_up.weight      | Block 12 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.12: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  121 | blk.13.attn_k.weight      | Block 13 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  122 | blk.13.attn_norm.weight   | Block 13 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  123 | blk.13.attn_output.weight | Block 13 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  124 | blk.13.attn_q.weight      | Block 13 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  125 | blk.13.attn_v.weight      | Block 13 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  126 | blk.13.ffn_down.weight    | Block 13 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  127 | blk.13.ffn_gate.weight    | Block 13 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  128 | blk.13.ffn_norm.weight    | Block 13 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  129 | blk.13.ffn_up.weight      | Block 13 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.13: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  130 | blk.14.attn_k.weight      | Block 14 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  131 | blk.14.attn_norm.weight   | Block 14 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  132 | blk.14.attn_output.weight | Block 14 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  133 | blk.14.attn_q.weight      | Block 14 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  134 | blk.14.attn_v.weight      | Block 14 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  135 | blk.14.ffn_down.weight    | Block 14 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  136 | blk.14.ffn_gate.weight    | Block 14 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  137 | blk.14.ffn_norm.weight    | Block 14 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  138 | blk.14.ffn_up.weight      | Block 14 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.14: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  139 | blk.15.attn_k.weight      | Block 15 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  140 | blk.15.attn_norm.weight   | Block 15 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  141 | blk.15.attn_output.weight | Block 15 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  142 | blk.15.attn_q.weight      | Block 15 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  143 | blk.15.attn_v.weight      | Block 15 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  144 | blk.15.ffn_down.weight    | Block 15 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  145 | blk.15.ffn_gate.weight    | Block 15 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  146 | blk.15.ffn_norm.weight    | Block 15 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  147 | blk.15.ffn_up.weight      | Block 15 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.15: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  148 | blk.16.attn_k.weight      | Block 16 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  149 | blk.16.attn_norm.weight   | Block 16 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  150 | blk.16.attn_output.weight | Block 16 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  151 | blk.16.attn_q.weight      | Block 16 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  152 | blk.16.attn_v.weight      | Block 16 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  153 | blk.16.ffn_down.weight    | Block 16 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  154 | blk.16.ffn_gate.weight    | Block 16 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  155 | blk.16.ffn_norm.weight    | Block 16 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  156 | blk.16.ffn_up.weight      | Block 16 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.16: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  157 | blk.17.attn_k.weight      | Block 17 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  158 | blk.17.attn_norm.weight   | Block 17 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  159 | blk.17.attn_output.weight | Block 17 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  160 | blk.17.attn_q.weight      | Block 17 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  161 | blk.17.attn_v.weight      | Block 17 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  162 | blk.17.ffn_down.weight    | Block 17 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  163 | blk.17.ffn_gate.weight    | Block 17 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  164 | blk.17.ffn_norm.weight    | Block 17 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  165 | blk.17.ffn_up.weight      | Block 17 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.17: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  166 | blk.18.attn_k.weight      | Block 18 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  167 | blk.18.attn_norm.weight   | Block 18 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  168 | blk.18.attn_output.weight | Block 18 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  169 | blk.18.attn_q.weight      | Block 18 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  170 | blk.18.attn_v.weight      | Block 18 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  171 | blk.18.ffn_down.weight    | Block 18 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  172 | blk.18.ffn_gate.weight    | Block 18 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  173 | blk.18.ffn_norm.weight    | Block 18 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  174 | blk.18.ffn_up.weight      | Block 18 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.18: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  175 | blk.19.attn_k.weight      | Block 19 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  176 | blk.19.attn_norm.weight   | Block 19 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  177 | blk.19.attn_output.weight | Block 19 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  178 | blk.19.attn_q.weight      | Block 19 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  179 | blk.19.attn_v.weight      | Block 19 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  180 | blk.19.ffn_down.weight    | Block 19 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  181 | blk.19.ffn_gate.weight    | Block 19 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  182 | blk.19.ffn_norm.weight    | Block 19 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  183 | blk.19.ffn_up.weight      | Block 19 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.19: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  184 | blk.20.attn_k.weight      | Block 20 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  185 | blk.20.attn_norm.weight   | Block 20 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  186 | blk.20.attn_output.weight | Block 20 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  187 | blk.20.attn_q.weight      | Block 20 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  188 | blk.20.attn_v.weight      | Block 20 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  189 | blk.20.ffn_down.weight    | Block 20 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  190 | blk.20.ffn_gate.weight    | Block 20 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  191 | blk.20.ffn_norm.weight    | Block 20 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  192 | blk.20.ffn_up.weight      | Block 20 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.20: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  193 | blk.21.attn_k.weight      | Block 21 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  194 | blk.21.attn_norm.weight   | Block 21 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  195 | blk.21.attn_output.weight | Block 21 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  196 | blk.21.attn_q.weight      | Block 21 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  197 | blk.21.attn_v.weight      | Block 21 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  198 | blk.21.ffn_down.weight    | Block 21 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  199 | blk.21.ffn_gate.weight    | Block 21 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  200 | blk.21.ffn_norm.weight    | Block 21 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  201 | blk.21.ffn_up.weight      | Block 21 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.21: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  202 | blk.22.attn_k.weight      | Block 22 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  203 | blk.22.attn_norm.weight   | Block 22 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  204 | blk.22.attn_output.weight | Block 22 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  205 | blk.22.attn_q.weight      | Block 22 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  206 | blk.22.attn_v.weight      | Block 22 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  207 | blk.22.ffn_down.weight    | Block 22 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  208 | blk.22.ffn_gate.weight    | Block 22 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  209 | blk.22.ffn_norm.weight    | Block 22 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  210 | blk.22.ffn_up.weight      | Block 22 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.22: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  211 | blk.23.attn_k.weight      | Block 23 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  212 | blk.23.attn_norm.weight   | Block 23 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  213 | blk.23.attn_output.weight | Block 23 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  214 | blk.23.attn_q.weight      | Block 23 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  215 | blk.23.attn_v.weight      | Block 23 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  216 | blk.23.ffn_down.weight    | Block 23 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  217 | blk.23.ffn_gate.weight    | Block 23 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  218 | blk.23.ffn_norm.weight    | Block 23 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  219 | blk.23.ffn_up.weight      | Block 23 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.23: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  220 | blk.24.attn_k.weight      | Block 24 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  221 | blk.24.attn_norm.weight   | Block 24 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  222 | blk.24.attn_output.weight | Block 24 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  223 | blk.24.attn_q.weight      | Block 24 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  224 | blk.24.attn_v.weight      | Block 24 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  225 | blk.24.ffn_down.weight    | Block 24 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  226 | blk.24.ffn_gate.weight    | Block 24 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  227 | blk.24.ffn_norm.weight    | Block 24 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  228 | blk.24.ffn_up.weight      | Block 24 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.24: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  229 | blk.25.attn_k.weight      | Block 25 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  230 | blk.25.attn_norm.weight   | Block 25 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  231 | blk.25.attn_output.weight | Block 25 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  232 | blk.25.attn_q.weight      | Block 25 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  233 | blk.25.attn_v.weight      | Block 25 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  234 | blk.25.ffn_down.weight    | Block 25 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  235 | blk.25.ffn_gate.weight    | Block 25 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  236 | blk.25.ffn_norm.weight    | Block 25 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  237 | blk.25.ffn_up.weight      | Block 25 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.25: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  238 | blk.26.attn_k.weight      | Block 26 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  239 | blk.26.attn_norm.weight   | Block 26 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  240 | blk.26.attn_output.weight | Block 26 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  241 | blk.26.attn_q.weight      | Block 26 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  242 | blk.26.attn_v.weight      | Block 26 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  243 | blk.26.ffn_down.weight    | Block 26 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  244 | blk.26.ffn_gate.weight    | Block 26 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  245 | blk.26.ffn_norm.weight    | Block 26 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  246 | blk.26.ffn_up.weight      | Block 26 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.26: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  247 | blk.27.attn_k.weight      | Block 27 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  248 | blk.27.attn_norm.weight   | Block 27 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  249 | blk.27.attn_output.weight | Block 27 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  250 | blk.27.attn_q.weight      | Block 27 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  251 | blk.27.attn_v.weight      | Block 27 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  252 | blk.27.ffn_down.weight    | Block 27 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  253 | blk.27.ffn_gate.weight    | Block 27 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  254 | blk.27.ffn_norm.weight    | Block 27 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  255 | blk.27.ffn_up.weight      | Block 27 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.27: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  256 | blk.28.attn_k.weight      | Block 28 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  257 | blk.28.attn_norm.weight   | Block 28 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  258 | blk.28.attn_output.weight | Block 28 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  259 | blk.28.attn_q.weight      | Block 28 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  260 | blk.28.attn_v.weight      | Block 28 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  261 | blk.28.ffn_down.weight    | Block 28 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  262 | blk.28.ffn_gate.weight    | Block 28 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  263 | blk.28.ffn_norm.weight    | Block 28 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  264 | blk.28.ffn_up.weight      | Block 28 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.28: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  265 | blk.29.attn_k.weight      | Block 29 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  266 | blk.29.attn_norm.weight   | Block 29 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  267 | blk.29.attn_output.weight | Block 29 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  268 | blk.29.attn_q.weight      | Block 29 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  269 | blk.29.attn_v.weight      | Block 29 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  270 | blk.29.ffn_down.weight    | Block 29 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  271 | blk.29.ffn_gate.weight    | Block 29 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  272 | blk.29.ffn_norm.weight    | Block 29 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  273 | blk.29.ffn_up.weight      | Block 29 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.29: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  274 | blk.30.attn_k.weight      | Block 30 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  275 | blk.30.attn_norm.weight   | Block 30 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  276 | blk.30.attn_output.weight | Block 30 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  277 | blk.30.attn_q.weight      | Block 30 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  278 | blk.30.attn_v.weight      | Block 30 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  279 | blk.30.ffn_down.weight    | Block 30 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  280 | blk.30.ffn_gate.weight    | Block 30 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  281 | blk.30.ffn_norm.weight    | Block 30 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  282 | blk.30.ffn_up.weight      | Block 30 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.30: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  283 | blk.31.attn_k.weight      | Block 31 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  284 | blk.31.attn_norm.weight   | Block 31 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  285 | blk.31.attn_output.weight | Block 31 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  286 | blk.31.attn_q.weight      | Block 31 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  287 | blk.31.attn_v.weight      | Block 31 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  288 | blk.31.ffn_down.weight    | Block 31 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  289 | blk.31.ffn_gate.weight    | Block 31 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  290 | blk.31.ffn_norm.weight    | Block 31 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  291 | blk.31.ffn_up.weight      | Block 31 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.31: (~218M) 218112000
+- Percentage of total elements: 2.72%

scores/Llama-Guard-3-8B-Q5_K_S.md ADDED Viewed

	@@ -0,0 +1,978 @@

+# Llama-Guard-3-8B-Q5_K_S.gguf - GGUF Internal File Dump
+- Endian: LITTLE endian
+## Key Value Metadata Store
+There are 39 key-value pairs in this file
+| POS | TYPE     |  Count | Key                                    | Value                                                               |
+|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
+|   1 | UINT32   |      1 | GGUF.version                           | 3                                                                   |
+|   2 | UINT64   |      1 | GGUF.tensor_count                      | 292                                                                 |
+|   3 | UINT64   |      1 | GGUF.kv_count                          | 36                                                                  |
+|   4 | STRING   |      1 | general.architecture                   | `llama`                                                             |
+|   5 | STRING   |      1 | general.type                           | `model`                                                             |
+|   6 | STRING   |      1 | general.name                           | `Llama Guard 3 8B`                                                  |
+|   7 | STRING   |      1 | general.basename                       | `Llama-Guard-3`                                                     |
+|   8 | STRING   |      1 | general.size_label                     | `8B`                                                                |
+|   9 | STRING   |      1 | general.license                        | `llama3.1`                                                          |
+|  10 | UINT32   |      1 | general.base_model.count               | 1                                                                   |
+|  11 | STRING   |      1 | general.base_model.0.name              | `Meta Llama 3.1 8B`                                                 |
+|  12 | STRING   |      1 | general.base_model.0.organization      | `Meta Llama`                                                        |
+|  13 | STRING   |      1 | general.base_model.0.repo_url          | `https://huggingface.co/meta-llama/Meta-Llama-3.1-8B`               |
+|  14 | [STRING] |      6 | general.tags                           | [ `facebook`, `meta`, `pytorch`, `llama`, `llama-3`, ... ]          |
+|  15 | [STRING] |      1 | general.languages                      | [ `en` ]                                                            |
+|  16 | UINT32   |      1 | llama.block_count                      | 32                                                                  |
+|  17 | UINT32   |      1 | llama.context_length                   | 131072                                                              |
+|  18 | UINT32   |      1 | llama.embedding_length                 | 4096                                                                |
+|  19 | UINT32   |      1 | llama.feed_forward_length              | 14336                                                               |
+|  20 | UINT32   |      1 | llama.attention.head_count             | 32                                                                  |
+|  21 | UINT32   |      1 | llama.attention.head_count_kv          | 8                                                                   |
+|  22 | FLOAT32  |      1 | llama.rope.freq_base                   | 500000.0                                                            |
+|  23 | FLOAT32  |      1 | llama.attention.layer_norm_rms_epsilon | 1e-05                                                               |
+|  24 | UINT32   |      1 | llama.vocab_size                       | 128256                                                              |
+|  25 | UINT32   |      1 | llama.rope.dimension_count             | 128                                                                 |
+|  26 | STRING   |      1 | tokenizer.ggml.model                   | `gpt2`                                                              |
+|  27 | STRING   |      1 | tokenizer.ggml.pre                     | `smaug-bpe`                                                         |
+|  28 | [STRING] | 128256 | tokenizer.ggml.tokens                  | [ `!`, `"`, `#`, `$`, `%`, ... ]                                    |
+|  29 | [INT32]  | 128256 | tokenizer.ggml.token_type              | [ 1, 1, 1, 1, 1, 1, 1, ... ]                                        |
+|  30 | [STRING] | 280147 | tokenizer.ggml.merges                  | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]                    |
+|  31 | UINT32   |      1 | tokenizer.ggml.bos_token_id            | 128000                                                              |
+|  32 | UINT32   |      1 | tokenizer.ggml.eos_token_id            | 128009                                                              |
+|  33 | STRING   |      1 | tokenizer.chat_template                | `{% if messages|length % 2 == 0`...`assistant<|end_header_id|>" }}` |
+|  34 | UINT32   |      1 | general.quantization_version           | 2                                                                   |
+|  35 | UINT32   |      1 | general.file_type                      | 16                                                                  |
+|  36 | STRING   |      1 | quantize.imatrix.file                  | `./imatrix/imatrix-Llama-Guard-3-8B-small.dat`                      |
+|  37 | STRING   |      1 | quantize.imatrix.dataset               | `../../datasets/imatrix/calibration_eur_small.txt`                  |
+|  38 | INT32    |      1 | quantize.imatrix.entries_count         | 224                                                                 |
+|  39 | INT32    |      1 | quantize.imatrix.chunks_count          | 962                                                                 |
+## Tensors Overview ~8B Elements
+Total number of elements in all tensors: 8030261312 Elements
+- [Llama-Guard-3-8B-Q5\_K\_S.gguf - GGUF Internal File Dump](#llama-guard-3-8b-q5_k_sgguf---gguf-internal-file-dump)
+  - [Key Value Metadata Store](#key-value-metadata-store)
+  - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
+    - [Tensor Data Offset](#tensor-data-offset)
+    - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
+    - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
+    - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
+    - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
+    - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
+    - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
+    - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
+    - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
+    - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
+    - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
+    - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
+    - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
+    - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
+    - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
+    - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
+    - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
+    - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
+    - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
+    - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
+    - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
+    - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
+    - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
+    - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
+    - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
+    - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
+    - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
+    - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
+    - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
+    - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
+    - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
+    - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
+    - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
+    - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
+### Tensor Data Offset
+This table contains the offset and data segment relative to start of file
+| T_ID | Tensor Layer Name         |  Data Offset (B) |    Data Size (B) |
+|-----:|:--------------------------|-----------------:|-----------------:|
+|    0 | output.weight             |         0x779880 |       0x15870000 |
+|    1 | output_norm.weight        |       0x15fe9880 |           0x4000 |
+|    2 | rope_freqs.weight         |       0x15fed880 |            0x100 |
+|    3 | token_embd.weight         |       0x15fed980 |        0xd746000 |
+|    4 | blk.0.attn_k.weight       |       0x23733980 |         0x240000 |
+|    5 | blk.0.attn_norm.weight    |       0x23973980 |           0x4000 |
+|    6 | blk.0.attn_output.weight  |       0x23977980 |         0xb00000 |
+|    7 | blk.0.attn_q.weight       |       0x24477980 |         0x900000 |
+|    8 | blk.0.attn_v.weight       |       0x24d77980 |         0x2c0000 |
+|    9 | blk.0.ffn_down.weight     |       0x25037980 |        0x2680000 |
+|   10 | blk.0.ffn_gate.weight     |       0x276b7980 |        0x1f80000 |
+|   11 | blk.0.ffn_norm.weight     |       0x29637980 |           0x4000 |
+|   12 | blk.0.ffn_up.weight       |       0x2963b980 |        0x1f80000 |
+|   13 | blk.1.attn_k.weight       |       0x2b5bb980 |         0x240000 |
+|   14 | blk.1.attn_norm.weight    |       0x2b7fb980 |           0x4000 |
+|   15 | blk.1.attn_output.weight  |       0x2b7ff980 |         0xb00000 |
+|   16 | blk.1.attn_q.weight       |       0x2c2ff980 |         0x900000 |
+|   17 | blk.1.attn_v.weight       |       0x2cbff980 |         0x2c0000 |
+|   18 | blk.1.ffn_down.weight     |       0x2cebf980 |        0x2df0000 |
+|   19 | blk.1.ffn_gate.weight     |       0x2fcaf980 |        0x1f80000 |
+|   20 | blk.1.ffn_norm.weight     |       0x31c2f980 |           0x4000 |
+|   21 | blk.1.ffn_up.weight       |       0x31c33980 |        0x1f80000 |
+|   22 | blk.2.attn_k.weight       |       0x33bb3980 |         0x240000 |
+|   23 | blk.2.attn_norm.weight    |       0x33df3980 |           0x4000 |
+|   24 | blk.2.attn_output.weight  |       0x33df7980 |         0xb00000 |
+|   25 | blk.2.attn_q.weight       |       0x348f7980 |         0x900000 |
+|   26 | blk.2.attn_v.weight       |       0x351f7980 |         0x2c0000 |
+|   27 | blk.2.ffn_down.weight     |       0x354b7980 |        0x2680000 |
+|   28 | blk.2.ffn_gate.weight     |       0x37b37980 |        0x1f80000 |
+|   29 | blk.2.ffn_norm.weight     |       0x39ab7980 |           0x4000 |
+|   30 | blk.2.ffn_up.weight       |       0x39abb980 |        0x1f80000 |
+|   31 | blk.3.attn_k.weight       |       0x3ba3b980 |         0x240000 |
+|   32 | blk.3.attn_norm.weight    |       0x3bc7b980 |           0x4000 |
+|   33 | blk.3.attn_output.weight  |       0x3bc7f980 |         0xb00000 |
+|   34 | blk.3.attn_q.weight       |       0x3c77f980 |         0x900000 |
+|   35 | blk.3.attn_v.weight       |       0x3d07f980 |         0x2c0000 |
+|   36 | blk.3.ffn_down.weight     |       0x3d33f980 |        0x2680000 |
+|   37 | blk.3.ffn_gate.weight     |       0x3f9bf980 |        0x1f80000 |
+|   38 | blk.3.ffn_norm.weight     |       0x4193f980 |           0x4000 |
+|   39 | blk.3.ffn_up.weight       |       0x41943980 |        0x1f80000 |
+|   40 | blk.4.attn_k.weight       |       0x438c3980 |         0x240000 |
+|   41 | blk.4.attn_norm.weight    |       0x43b03980 |           0x4000 |
+|   42 | blk.4.attn_output.weight  |       0x43b07980 |         0xb00000 |
+|   43 | blk.4.attn_q.weight       |       0x44607980 |         0x900000 |
+|   44 | blk.4.attn_v.weight       |       0x44f07980 |         0x2c0000 |
+|   45 | blk.4.ffn_down.weight     |       0x451c7980 |        0x2680000 |
+|   46 | blk.4.ffn_gate.weight     |       0x47847980 |        0x1f80000 |
+|   47 | blk.4.ffn_norm.weight     |       0x497c7980 |           0x4000 |
+|   48 | blk.4.ffn_up.weight       |       0x497cb980 |        0x1f80000 |
+|   49 | blk.5.attn_k.weight       |       0x4b74b980 |         0x240000 |
+|   50 | blk.5.attn_norm.weight    |       0x4b98b980 |           0x4000 |
+|   51 | blk.5.attn_output.weight  |       0x4b98f980 |         0xb00000 |
+|   52 | blk.5.attn_q.weight       |       0x4c48f980 |         0x900000 |
+|   53 | blk.5.attn_v.weight       |       0x4cd8f980 |         0x2c0000 |
+|   54 | blk.5.ffn_down.weight     |       0x4d04f980 |        0x2680000 |
+|   55 | blk.5.ffn_gate.weight     |       0x4f6cf980 |        0x1f80000 |
+|   56 | blk.5.ffn_norm.weight     |       0x5164f980 |           0x4000 |
+|   57 | blk.5.ffn_up.weight       |       0x51653980 |        0x1f80000 |
+|   58 | blk.6.attn_k.weight       |       0x535d3980 |         0x240000 |
+|   59 | blk.6.attn_norm.weight    |       0x53813980 |           0x4000 |
+|   60 | blk.6.attn_output.weight  |       0x53817980 |         0xb00000 |
+|   61 | blk.6.attn_q.weight       |       0x54317980 |         0x900000 |
+|   62 | blk.6.attn_v.weight       |       0x54c17980 |         0x2c0000 |
+|   63 | blk.6.ffn_down.weight     |       0x54ed7980 |        0x2680000 |
+|   64 | blk.6.ffn_gate.weight     |       0x57557980 |        0x1f80000 |
+|   65 | blk.6.ffn_norm.weight     |       0x594d7980 |           0x4000 |
+|   66 | blk.6.ffn_up.weight       |       0x594db980 |        0x1f80000 |
+|   67 | blk.7.attn_k.weight       |       0x5b45b980 |         0x240000 |
+|   68 | blk.7.attn_norm.weight    |       0x5b69b980 |           0x4000 |
+|   69 | blk.7.attn_output.weight  |       0x5b69f980 |         0xb00000 |
+|   70 | blk.7.attn_q.weight       |       0x5c19f980 |         0x900000 |
+|   71 | blk.7.attn_v.weight       |       0x5ca9f980 |         0x2c0000 |
+|   72 | blk.7.ffn_down.weight     |       0x5cd5f980 |        0x2680000 |
+|   73 | blk.7.ffn_gate.weight     |       0x5f3df980 |        0x1f80000 |
+|   74 | blk.7.ffn_norm.weight     |       0x6135f980 |           0x4000 |
+|   75 | blk.7.ffn_up.weight       |       0x61363980 |        0x1f80000 |
+|   76 | blk.8.attn_k.weight       |       0x632e3980 |         0x240000 |
+|   77 | blk.8.attn_norm.weight    |       0x63523980 |           0x4000 |
+|   78 | blk.8.attn_output.weight  |       0x63527980 |         0xb00000 |
+|   79 | blk.8.attn_q.weight       |       0x64027980 |         0x900000 |
+|   80 | blk.8.attn_v.weight       |       0x64927980 |         0x2c0000 |
+|   81 | blk.8.ffn_down.weight     |       0x64be7980 |        0x2680000 |
+|   82 | blk.8.ffn_gate.weight     |       0x67267980 |        0x1f80000 |
+|   83 | blk.8.ffn_norm.weight     |       0x691e7980 |           0x4000 |
+|   84 | blk.8.ffn_up.weight       |       0x691eb980 |        0x1f80000 |
+|   85 | blk.9.attn_k.weight       |       0x6b16b980 |         0x240000 |
+|   86 | blk.9.attn_norm.weight    |       0x6b3ab980 |           0x4000 |
+|   87 | blk.9.attn_output.weight  |       0x6b3af980 |         0xb00000 |
+|   88 | blk.9.attn_q.weight       |       0x6beaf980 |         0x900000 |
+|   89 | blk.9.attn_v.weight       |       0x6c7af980 |         0x2c0000 |
+|   90 | blk.9.ffn_down.weight     |       0x6ca6f980 |        0x2680000 |
+|   91 | blk.9.ffn_gate.weight     |       0x6f0ef980 |        0x1f80000 |
+|   92 | blk.9.ffn_norm.weight     |       0x7106f980 |           0x4000 |
+|   93 | blk.9.ffn_up.weight       |       0x71073980 |        0x1f80000 |
+|   94 | blk.10.attn_k.weight      |       0x72ff3980 |         0x240000 |
+|   95 | blk.10.attn_norm.weight   |       0x73233980 |           0x4000 |
+|   96 | blk.10.attn_output.weight |       0x73237980 |         0xb00000 |
+|   97 | blk.10.attn_q.weight      |       0x73d37980 |         0x900000 |
+|   98 | blk.10.attn_v.weight      |       0x74637980 |         0x2c0000 |
+|   99 | blk.10.ffn_down.weight    |       0x748f7980 |        0x2680000 |
+|  100 | blk.10.ffn_gate.weight    |       0x76f77980 |        0x1f80000 |
+|  101 | blk.10.ffn_norm.weight    |       0x78ef7980 |           0x4000 |
+|  102 | blk.10.ffn_up.weight      |       0x78efb980 |        0x1f80000 |
+|  103 | blk.11.attn_k.weight      |       0x7ae7b980 |         0x240000 |
+|  104 | blk.11.attn_norm.weight   |       0x7b0bb980 |           0x4000 |
+|  105 | blk.11.attn_output.weight |       0x7b0bf980 |         0xb00000 |
+|  106 | blk.11.attn_q.weight      |       0x7bbbf980 |         0x900000 |
+|  107 | blk.11.attn_v.weight      |       0x7c4bf980 |         0x2c0000 |
+|  108 | blk.11.ffn_down.weight    |       0x7c77f980 |        0x2680000 |
+|  109 | blk.11.ffn_gate.weight    |       0x7edff980 |        0x1f80000 |
+|  110 | blk.11.ffn_norm.weight    |       0x80d7f980 |           0x4000 |
+|  111 | blk.11.ffn_up.weight      |       0x80d83980 |        0x1f80000 |
+|  112 | blk.12.attn_k.weight      |       0x82d03980 |         0x240000 |
+|  113 | blk.12.attn_norm.weight   |       0x82f43980 |           0x4000 |
+|  114 | blk.12.attn_output.weight |       0x82f47980 |         0xb00000 |
+|  115 | blk.12.attn_q.weight      |       0x83a47980 |         0x900000 |
+|  116 | blk.12.attn_v.weight      |       0x84347980 |         0x2c0000 |
+|  117 | blk.12.ffn_down.weight    |       0x84607980 |        0x2680000 |
+|  118 | blk.12.ffn_gate.weight    |       0x86c87980 |        0x1f80000 |
+|  119 | blk.12.ffn_norm.weight    |       0x88c07980 |           0x4000 |
+|  120 | blk.12.ffn_up.weight      |       0x88c0b980 |        0x1f80000 |
+|  121 | blk.13.attn_k.weight      |       0x8ab8b980 |         0x2c0000 |
+|  122 | blk.13.attn_norm.weight   |       0x8ae4b980 |           0x4000 |
+|  123 | blk.13.attn_output.weight |       0x8ae4f980 |         0xb00000 |
+|  124 | blk.13.attn_q.weight      |       0x8b94f980 |         0xb00000 |
+|  125 | blk.13.attn_v.weight      |       0x8c44f980 |         0x2c0000 |
+|  126 | blk.13.ffn_down.weight    |       0x8c70f980 |        0x2680000 |
+|  127 | blk.13.ffn_gate.weight    |       0x8ed8f980 |        0x1f80000 |
+|  128 | blk.13.ffn_norm.weight    |       0x90d0f980 |           0x4000 |
+|  129 | blk.13.ffn_up.weight      |       0x90d13980 |        0x1f80000 |
+|  130 | blk.14.attn_k.weight      |       0x92c93980 |         0x2c0000 |
+|  131 | blk.14.attn_norm.weight   |       0x92f53980 |           0x4000 |
+|  132 | blk.14.attn_output.weight |       0x92f57980 |         0xb00000 |
+|  133 | blk.14.attn_q.weight      |       0x93a57980 |         0xb00000 |
+|  134 | blk.14.attn_v.weight      |       0x94557980 |         0x2c0000 |
+|  135 | blk.14.ffn_down.weight    |       0x94817980 |        0x2680000 |
+|  136 | blk.14.ffn_gate.weight    |       0x96e97980 |        0x1f80000 |
+|  137 | blk.14.ffn_norm.weight    |       0x98e17980 |           0x4000 |
+|  138 | blk.14.ffn_up.weight      |       0x98e1b980 |        0x1f80000 |
+|  139 | blk.15.attn_k.weight      |       0x9ad9b980 |         0x240000 |
+|  140 | blk.15.attn_norm.weight   |       0x9afdb980 |           0x4000 |
+|  141 | blk.15.attn_output.weight |       0x9afdf980 |         0xb00000 |
+|  142 | blk.15.attn_q.weight      |       0x9badf980 |         0x900000 |
+|  143 | blk.15.attn_v.weight      |       0x9c3df980 |         0x2c0000 |
+|  144 | blk.15.ffn_down.weight    |       0x9c69f980 |        0x2680000 |
+|  145 | blk.15.ffn_gate.weight    |       0x9ed1f980 |        0x1f80000 |
+|  146 | blk.15.ffn_norm.weight    |       0xa0c9f980 |           0x4000 |
+|  147 | blk.15.ffn_up.weight      |       0xa0ca3980 |        0x1f80000 |
+|  148 | blk.16.attn_k.weight      |       0xa2c23980 |         0x2c0000 |
+|  149 | blk.16.attn_norm.weight   |       0xa2ee3980 |           0x4000 |
+|  150 | blk.16.attn_output.weight |       0xa2ee7980 |         0xb00000 |
+|  151 | blk.16.attn_q.weight      |       0xa39e7980 |         0xb00000 |
+|  152 | blk.16.attn_v.weight      |       0xa44e7980 |         0x2c0000 |
+|  153 | blk.16.ffn_down.weight    |       0xa47a7980 |        0x2680000 |
+|  154 | blk.16.ffn_gate.weight    |       0xa6e27980 |        0x2680000 |
+|  155 | blk.16.ffn_norm.weight    |       0xa94a7980 |           0x4000 |
+|  156 | blk.16.ffn_up.weight      |       0xa94ab980 |        0x2680000 |
+|  157 | blk.17.attn_k.weight      |       0xabb2b980 |         0x240000 |
+|  158 | blk.17.attn_norm.weight   |       0xabd6b980 |           0x4000 |
+|  159 | blk.17.attn_output.weight |       0xabd6f980 |         0xb00000 |
+|  160 | blk.17.attn_q.weight      |       0xac86f980 |         0x900000 |
+|  161 | blk.17.attn_v.weight      |       0xad16f980 |         0x2c0000 |
+|  162 | blk.17.ffn_down.weight    |       0xad42f980 |        0x2df0000 |
+|  163 | blk.17.ffn_gate.weight    |       0xb021f980 |        0x2680000 |
+|  164 | blk.17.ffn_norm.weight    |       0xb289f980 |           0x4000 |
+|  165 | blk.17.ffn_up.weight      |       0xb28a3980 |        0x2680000 |
+|  166 | blk.18.attn_k.weight      |       0xb4f23980 |         0x2c0000 |
+|  167 | blk.18.attn_norm.weight   |       0xb51e3980 |           0x4000 |
+|  168 | blk.18.attn_output.weight |       0xb51e7980 |         0xb00000 |
+|  169 | blk.18.attn_q.weight      |       0xb5ce7980 |         0xb00000 |
+|  170 | blk.18.attn_v.weight      |       0xb67e7980 |         0x2c0000 |
+|  171 | blk.18.ffn_down.weight    |       0xb6aa7980 |        0x2df0000 |
+|  172 | blk.18.ffn_gate.weight    |       0xb9897980 |        0x2680000 |
+|  173 | blk.18.ffn_norm.weight    |       0xbbf17980 |           0x4000 |
+|  174 | blk.18.ffn_up.weight      |       0xbbf1b980 |        0x2680000 |
+|  175 | blk.19.attn_k.weight      |       0xbe59b980 |         0x2c0000 |
+|  176 | blk.19.attn_norm.weight   |       0xbe85b980 |           0x4000 |
+|  177 | blk.19.attn_output.weight |       0xbe85f980 |         0xb00000 |
+|  178 | blk.19.attn_q.weight      |       0xbf35f980 |         0xb00000 |
+|  179 | blk.19.attn_v.weight      |       0xbfe5f980 |         0x2c0000 |
+|  180 | blk.19.ffn_down.weight    |       0xc011f980 |        0x2df0000 |
+|  181 | blk.19.ffn_gate.weight    |       0xc2f0f980 |        0x2680000 |
+|  182 | blk.19.ffn_norm.weight    |       0xc558f980 |           0x4000 |
+|  183 | blk.19.ffn_up.weight      |       0xc5593980 |        0x2680000 |
+|  184 | blk.20.attn_k.weight      |       0xc7c13980 |         0x2c0000 |
+|  185 | blk.20.attn_norm.weight   |       0xc7ed3980 |           0x4000 |
+|  186 | blk.20.attn_output.weight |       0xc7ed7980 |         0xb00000 |
+|  187 | blk.20.attn_q.weight      |       0xc89d7980 |         0xb00000 |
+|  188 | blk.20.attn_v.weight      |       0xc94d7980 |         0x2c0000 |
+|  189 | blk.20.ffn_down.weight    |       0xc9797980 |        0x2df0000 |
+|  190 | blk.20.ffn_gate.weight    |       0xcc587980 |        0x2680000 |
+|  191 | blk.20.ffn_norm.weight    |       0xcec07980 |           0x4000 |
+|  192 | blk.20.ffn_up.weight      |       0xcec0b980 |        0x2680000 |
+|  193 | blk.21.attn_k.weight      |       0xd128b980 |         0x2c0000 |
+|  194 | blk.21.attn_norm.weight   |       0xd154b980 |           0x4000 |
+|  195 | blk.21.attn_output.weight |       0xd154f980 |         0xb00000 |
+|  196 | blk.21.attn_q.weight      |       0xd204f980 |         0xb00000 |
+|  197 | blk.21.attn_v.weight      |       0xd2b4f980 |         0x2c0000 |
+|  198 | blk.21.ffn_down.weight    |       0xd2e0f980 |        0x2df0000 |
+|  199 | blk.21.ffn_gate.weight    |       0xd5bff980 |        0x2680000 |
+|  200 | blk.21.ffn_norm.weight    |       0xd827f980 |           0x4000 |
+|  201 | blk.21.ffn_up.weight      |       0xd8283980 |        0x2680000 |
+|  202 | blk.22.attn_k.weight      |       0xda903980 |         0x2c0000 |
+|  203 | blk.22.attn_norm.weight   |       0xdabc3980 |           0x4000 |
+|  204 | blk.22.attn_output.weight |       0xdabc7980 |         0xb00000 |
+|  205 | blk.22.attn_q.weight      |       0xdb6c7980 |         0xb00000 |
+|  206 | blk.22.attn_v.weight      |       0xdc1c7980 |         0x2c0000 |
+|  207 | blk.22.ffn_down.weight    |       0xdc487980 |        0x2df0000 |
+|  208 | blk.22.ffn_gate.weight    |       0xdf277980 |        0x2680000 |
+|  209 | blk.22.ffn_norm.weight    |       0xe18f7980 |           0x4000 |
+|  210 | blk.22.ffn_up.weight      |       0xe18fb980 |        0x2680000 |
+|  211 | blk.23.attn_k.weight      |       0xe3f7b980 |         0x2c0000 |
+|  212 | blk.23.attn_norm.weight   |       0xe423b980 |           0x4000 |
+|  213 | blk.23.attn_output.weight |       0xe423f980 |         0xb00000 |
+|  214 | blk.23.attn_q.weight      |       0xe4d3f980 |         0xb00000 |
+|  215 | blk.23.attn_v.weight      |       0xe583f980 |         0x2c0000 |
+|  216 | blk.23.ffn_down.weight    |       0xe5aff980 |        0x2df0000 |
+|  217 | blk.23.ffn_gate.weight    |       0xe88ef980 |        0x2680000 |
+|  218 | blk.23.ffn_norm.weight    |       0xeaf6f980 |           0x4000 |
+|  219 | blk.23.ffn_up.weight      |       0xeaf73980 |        0x2680000 |
+|  220 | blk.24.attn_k.weight      |       0xed5f3980 |         0x2c0000 |
+|  221 | blk.24.attn_norm.weight   |       0xed8b3980 |           0x4000 |
+|  222 | blk.24.attn_output.weight |       0xed8b7980 |         0xb00000 |
+|  223 | blk.24.attn_q.weight      |       0xee3b7980 |         0xb00000 |
+|  224 | blk.24.attn_v.weight      |       0xeeeb7980 |         0x2c0000 |
+|  225 | blk.24.ffn_down.weight    |       0xef177980 |        0x2df0000 |
+|  226 | blk.24.ffn_gate.weight    |       0xf1f67980 |        0x2680000 |
+|  227 | blk.24.ffn_norm.weight    |       0xf45e7980 |           0x4000 |
+|  228 | blk.24.ffn_up.weight      |       0xf45eb980 |        0x2680000 |
+|  229 | blk.25.attn_k.weight      |       0xf6c6b980 |         0x2c0000 |
+|  230 | blk.25.attn_norm.weight   |       0xf6f2b980 |           0x4000 |
+|  231 | blk.25.attn_output.weight |       0xf6f2f980 |         0xb00000 |
+|  232 | blk.25.attn_q.weight      |       0xf7a2f980 |         0xb00000 |
+|  233 | blk.25.attn_v.weight      |       0xf852f980 |         0x2c0000 |
+|  234 | blk.25.ffn_down.weight    |       0xf87ef980 |        0x2df0000 |
+|  235 | blk.25.ffn_gate.weight    |       0xfb5df980 |        0x2680000 |
+|  236 | blk.25.ffn_norm.weight    |       0xfdc5f980 |           0x4000 |
+|  237 | blk.25.ffn_up.weight      |       0xfdc63980 |        0x2680000 |
+|  238 | blk.26.attn_k.weight      |      0x1002e3980 |         0x2c0000 |
+|  239 | blk.26.attn_norm.weight   |      0x1005a3980 |           0x4000 |
+|  240 | blk.26.attn_output.weight |      0x1005a7980 |         0xb00000 |
+|  241 | blk.26.attn_q.weight      |      0x1010a7980 |         0xb00000 |
+|  242 | blk.26.attn_v.weight      |      0x101ba7980 |         0x2c0000 |
+|  243 | blk.26.ffn_down.weight    |      0x101e67980 |        0x2df0000 |
+|  244 | blk.26.ffn_gate.weight    |      0x104c57980 |        0x2680000 |
+|  245 | blk.26.ffn_norm.weight    |      0x1072d7980 |           0x4000 |
+|  246 | blk.26.ffn_up.weight      |      0x1072db980 |        0x2680000 |
+|  247 | blk.27.attn_k.weight      |      0x10995b980 |         0x2c0000 |
+|  248 | blk.27.attn_norm.weight   |      0x109c1b980 |           0x4000 |
+|  249 | blk.27.attn_output.weight |      0x109c1f980 |         0xb00000 |
+|  250 | blk.27.attn_q.weight      |      0x10a71f980 |         0xb00000 |
+|  251 | blk.27.attn_v.weight      |      0x10b21f980 |         0x2c0000 |
+|  252 | blk.27.ffn_down.weight    |      0x10b4df980 |        0x2df0000 |
+|  253 | blk.27.ffn_gate.weight    |      0x10e2cf980 |        0x2680000 |
+|  254 | blk.27.ffn_norm.weight    |      0x11094f980 |           0x4000 |
+|  255 | blk.27.ffn_up.weight      |      0x110953980 |        0x2680000 |
+|  256 | blk.28.attn_k.weight      |      0x112fd3980 |         0x2c0000 |
+|  257 | blk.28.attn_norm.weight   |      0x113293980 |           0x4000 |
+|  258 | blk.28.attn_output.weight |      0x113297980 |         0xb00000 |
+|  259 | blk.28.attn_q.weight      |      0x113d97980 |         0xb00000 |
+|  260 | blk.28.attn_v.weight      |      0x114897980 |         0x2c0000 |
+|  261 | blk.28.ffn_down.weight    |      0x114b57980 |        0x2df0000 |
+|  262 | blk.28.ffn_gate.weight    |      0x117947980 |        0x2680000 |
+|  263 | blk.28.ffn_norm.weight    |      0x119fc7980 |           0x4000 |
+|  264 | blk.28.ffn_up.weight      |      0x119fcb980 |        0x2680000 |
+|  265 | blk.29.attn_k.weight      |      0x11c64b980 |         0x2c0000 |
+|  266 | blk.29.attn_norm.weight   |      0x11c90b980 |           0x4000 |
+|  267 | blk.29.attn_output.weight |      0x11c90f980 |         0xb00000 |
+|  268 | blk.29.attn_q.weight      |      0x11d40f980 |         0xb00000 |
+|  269 | blk.29.attn_v.weight      |      0x11df0f980 |         0x2c0000 |
+|  270 | blk.29.ffn_down.weight    |      0x11e1cf980 |        0x2df0000 |
+|  271 | blk.29.ffn_gate.weight    |      0x120fbf980 |        0x2680000 |
+|  272 | blk.29.ffn_norm.weight    |      0x12363f980 |           0x4000 |
+|  273 | blk.29.ffn_up.weight      |      0x123643980 |        0x2680000 |
+|  274 | blk.30.attn_k.weight      |      0x125cc3980 |         0x2c0000 |
+|  275 | blk.30.attn_norm.weight   |      0x125f83980 |           0x4000 |
+|  276 | blk.30.attn_output.weight |      0x125f87980 |         0xb00000 |
+|  277 | blk.30.attn_q.weight      |      0x126a87980 |         0xb00000 |
+|  278 | blk.30.attn_v.weight      |      0x127587980 |         0x2c0000 |
+|  279 | blk.30.ffn_down.weight    |      0x127847980 |        0x2df0000 |
+|  280 | blk.30.ffn_gate.weight    |      0x12a637980 |        0x2680000 |
+|  281 | blk.30.ffn_norm.weight    |      0x12ccb7980 |           0x4000 |
+|  282 | blk.30.ffn_up.weight      |      0x12ccbb980 |        0x2680000 |
+|  283 | blk.31.attn_k.weight      |      0x12f33b980 |         0x240000 |
+|  284 | blk.31.attn_norm.weight   |      0x12f57b980 |           0x4000 |
+|  285 | blk.31.attn_output.weight |      0x12f57f980 |         0xb00000 |
+|  286 | blk.31.attn_q.weight      |      0x13007f980 |         0x900000 |
+|  287 | blk.31.attn_v.weight      |      0x13097f980 |         0x2c0000 |
+|  288 | blk.31.ffn_down.weight    |      0x130c3f980 |        0x2df0000 |
+|  289 | blk.31.ffn_gate.weight    |      0x133a2f980 |        0x2680000 |
+|  290 | blk.31.ffn_norm.weight    |      0x1360af980 |           0x4000 |
+|  291 | blk.31.ffn_up.weight      |      0x1360b3980 |        0x2680000 |
+### <a name="base">Base Tensor Group : ~1B Elements</a>
+| T_ID | Tensor Layer Name  | Human Friendly Tensor Layer Name | Elements          | Shape                 | Type |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
+|    0 | output.weight      | Output (W)                       | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q5_K |
+|    1 | output_norm.weight | Output Normalization (W)         | (  ~4K)      4096 | 4096 x      1 x 1 x 1 | F32  |
+|    2 | rope_freqs.weight  | Rope_Freqs (W)                   | (   64)        64 |   64 x      1 x 1 x 1 | F32  |
+|    3 | token_embd.weight  | Token Embedding (W)              | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q3_K |
+- Total elements in base: ( ~1B) 1050677312
+- Percentage of total elements: 13.08%
+### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|    4 | blk.0.attn_k.weight      | Block 0 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|    5 | blk.0.attn_norm.weight   | Block 0 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|    6 | blk.0.attn_output.weight | Block 0 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|    7 | blk.0.attn_q.weight      | Block 0 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|    8 | blk.0.attn_v.weight      | Block 0 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|    9 | blk.0.ffn_down.weight    | Block 0 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   10 | blk.0.ffn_gate.weight    | Block 0 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   11 | blk.0.ffn_norm.weight    | Block 0 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   12 | blk.0.ffn_up.weight      | Block 0 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.0: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   13 | blk.1.attn_k.weight      | Block 1 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   14 | blk.1.attn_norm.weight   | Block 1 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   15 | blk.1.attn_output.weight | Block 1 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   16 | blk.1.attn_q.weight      | Block 1 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   17 | blk.1.attn_v.weight      | Block 1 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   18 | blk.1.ffn_down.weight    | Block 1 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|   19 | blk.1.ffn_gate.weight    | Block 1 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   20 | blk.1.ffn_norm.weight    | Block 1 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   21 | blk.1.ffn_up.weight      | Block 1 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.1: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   22 | blk.2.attn_k.weight      | Block 2 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   23 | blk.2.attn_norm.weight   | Block 2 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   24 | blk.2.attn_output.weight | Block 2 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   25 | blk.2.attn_q.weight      | Block 2 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   26 | blk.2.attn_v.weight      | Block 2 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   27 | blk.2.ffn_down.weight    | Block 2 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   28 | blk.2.ffn_gate.weight    | Block 2 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   29 | blk.2.ffn_norm.weight    | Block 2 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   30 | blk.2.ffn_up.weight      | Block 2 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.2: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   31 | blk.3.attn_k.weight      | Block 3 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   32 | blk.3.attn_norm.weight   | Block 3 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   33 | blk.3.attn_output.weight | Block 3 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   34 | blk.3.attn_q.weight      | Block 3 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   35 | blk.3.attn_v.weight      | Block 3 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   36 | blk.3.ffn_down.weight    | Block 3 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   37 | blk.3.ffn_gate.weight    | Block 3 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   38 | blk.3.ffn_norm.weight    | Block 3 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   39 | blk.3.ffn_up.weight      | Block 3 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.3: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   40 | blk.4.attn_k.weight      | Block 4 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   41 | blk.4.attn_norm.weight   | Block 4 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   42 | blk.4.attn_output.weight | Block 4 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   43 | blk.4.attn_q.weight      | Block 4 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   44 | blk.4.attn_v.weight      | Block 4 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   45 | blk.4.ffn_down.weight    | Block 4 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   46 | blk.4.ffn_gate.weight    | Block 4 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   47 | blk.4.ffn_norm.weight    | Block 4 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   48 | blk.4.ffn_up.weight      | Block 4 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.4: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   49 | blk.5.attn_k.weight      | Block 5 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   50 | blk.5.attn_norm.weight   | Block 5 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   51 | blk.5.attn_output.weight | Block 5 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   52 | blk.5.attn_q.weight      | Block 5 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   53 | blk.5.attn_v.weight      | Block 5 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   54 | blk.5.ffn_down.weight    | Block 5 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   55 | blk.5.ffn_gate.weight    | Block 5 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   56 | blk.5.ffn_norm.weight    | Block 5 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   57 | blk.5.ffn_up.weight      | Block 5 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.5: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   58 | blk.6.attn_k.weight      | Block 6 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   59 | blk.6.attn_norm.weight   | Block 6 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   60 | blk.6.attn_output.weight | Block 6 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   61 | blk.6.attn_q.weight      | Block 6 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   62 | blk.6.attn_v.weight      | Block 6 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   63 | blk.6.ffn_down.weight    | Block 6 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   64 | blk.6.ffn_gate.weight    | Block 6 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   65 | blk.6.ffn_norm.weight    | Block 6 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   66 | blk.6.ffn_up.weight      | Block 6 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.6: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   67 | blk.7.attn_k.weight      | Block 7 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   68 | blk.7.attn_norm.weight   | Block 7 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   69 | blk.7.attn_output.weight | Block 7 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   70 | blk.7.attn_q.weight      | Block 7 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   71 | blk.7.attn_v.weight      | Block 7 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   72 | blk.7.ffn_down.weight    | Block 7 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   73 | blk.7.ffn_gate.weight    | Block 7 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   74 | blk.7.ffn_norm.weight    | Block 7 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   75 | blk.7.ffn_up.weight      | Block 7 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.7: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   76 | blk.8.attn_k.weight      | Block 8 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   77 | blk.8.attn_norm.weight   | Block 8 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   78 | blk.8.attn_output.weight | Block 8 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   79 | blk.8.attn_q.weight      | Block 8 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   80 | blk.8.attn_v.weight      | Block 8 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   81 | blk.8.ffn_down.weight    | Block 8 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   82 | blk.8.ffn_gate.weight    | Block 8 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   83 | blk.8.ffn_norm.weight    | Block 8 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   84 | blk.8.ffn_up.weight      | Block 8 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.8: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   85 | blk.9.attn_k.weight      | Block 9 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   86 | blk.9.attn_norm.weight   | Block 9 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   87 | blk.9.attn_output.weight | Block 9 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   88 | blk.9.attn_q.weight      | Block 9 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   89 | blk.9.attn_v.weight      | Block 9 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   90 | blk.9.ffn_down.weight    | Block 9 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|   91 | blk.9.ffn_gate.weight    | Block 9 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|   92 | blk.9.ffn_norm.weight    | Block 9 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   93 | blk.9.ffn_up.weight      | Block 9 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.9: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|   94 | blk.10.attn_k.weight      | Block 10 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|   95 | blk.10.attn_norm.weight   | Block 10 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   96 | blk.10.attn_output.weight | Block 10 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   97 | blk.10.attn_q.weight      | Block 10 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|   98 | blk.10.attn_v.weight      | Block 10 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   99 | blk.10.ffn_down.weight    | Block 10 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  100 | blk.10.ffn_gate.weight    | Block 10 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  101 | blk.10.ffn_norm.weight    | Block 10 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  102 | blk.10.ffn_up.weight      | Block 10 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.10: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  103 | blk.11.attn_k.weight      | Block 11 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  104 | blk.11.attn_norm.weight   | Block 11 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  105 | blk.11.attn_output.weight | Block 11 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  106 | blk.11.attn_q.weight      | Block 11 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  107 | blk.11.attn_v.weight      | Block 11 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  108 | blk.11.ffn_down.weight    | Block 11 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  109 | blk.11.ffn_gate.weight    | Block 11 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  110 | blk.11.ffn_norm.weight    | Block 11 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  111 | blk.11.ffn_up.weight      | Block 11 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.11: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  112 | blk.12.attn_k.weight      | Block 12 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  113 | blk.12.attn_norm.weight   | Block 12 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  114 | blk.12.attn_output.weight | Block 12 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  115 | blk.12.attn_q.weight      | Block 12 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  116 | blk.12.attn_v.weight      | Block 12 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  117 | blk.12.ffn_down.weight    | Block 12 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  118 | blk.12.ffn_gate.weight    | Block 12 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  119 | blk.12.ffn_norm.weight    | Block 12 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  120 | blk.12.ffn_up.weight      | Block 12 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.12: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  121 | blk.13.attn_k.weight      | Block 13 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  122 | blk.13.attn_norm.weight   | Block 13 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  123 | blk.13.attn_output.weight | Block 13 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  124 | blk.13.attn_q.weight      | Block 13 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  125 | blk.13.attn_v.weight      | Block 13 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  126 | blk.13.ffn_down.weight    | Block 13 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  127 | blk.13.ffn_gate.weight    | Block 13 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  128 | blk.13.ffn_norm.weight    | Block 13 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  129 | blk.13.ffn_up.weight      | Block 13 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.13: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  130 | blk.14.attn_k.weight      | Block 14 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  131 | blk.14.attn_norm.weight   | Block 14 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  132 | blk.14.attn_output.weight | Block 14 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  133 | blk.14.attn_q.weight      | Block 14 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  134 | blk.14.attn_v.weight      | Block 14 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  135 | blk.14.ffn_down.weight    | Block 14 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  136 | blk.14.ffn_gate.weight    | Block 14 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  137 | blk.14.ffn_norm.weight    | Block 14 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  138 | blk.14.ffn_up.weight      | Block 14 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.14: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  139 | blk.15.attn_k.weight      | Block 15 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  140 | blk.15.attn_norm.weight   | Block 15 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  141 | blk.15.attn_output.weight | Block 15 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  142 | blk.15.attn_q.weight      | Block 15 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  143 | blk.15.attn_v.weight      | Block 15 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  144 | blk.15.ffn_down.weight    | Block 15 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  145 | blk.15.ffn_gate.weight    | Block 15 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+|  146 | blk.15.ffn_norm.weight    | Block 15 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  147 | blk.15.ffn_up.weight      | Block 15 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q4_K |
+- Total elements in blk.15: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  148 | blk.16.attn_k.weight      | Block 16 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  149 | blk.16.attn_norm.weight   | Block 16 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  150 | blk.16.attn_output.weight | Block 16 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  151 | blk.16.attn_q.weight      | Block 16 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  152 | blk.16.attn_v.weight      | Block 16 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  153 | blk.16.ffn_down.weight    | Block 16 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q5_K |
+|  154 | blk.16.ffn_gate.weight    | Block 16 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  155 | blk.16.ffn_norm.weight    | Block 16 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  156 | blk.16.ffn_up.weight      | Block 16 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.16: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  157 | blk.17.attn_k.weight      | Block 17 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  158 | blk.17.attn_norm.weight   | Block 17 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  159 | blk.17.attn_output.weight | Block 17 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  160 | blk.17.attn_q.weight      | Block 17 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  161 | blk.17.attn_v.weight      | Block 17 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  162 | blk.17.ffn_down.weight    | Block 17 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  163 | blk.17.ffn_gate.weight    | Block 17 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  164 | blk.17.ffn_norm.weight    | Block 17 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  165 | blk.17.ffn_up.weight      | Block 17 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.17: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  166 | blk.18.attn_k.weight      | Block 18 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  167 | blk.18.attn_norm.weight   | Block 18 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  168 | blk.18.attn_output.weight | Block 18 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  169 | blk.18.attn_q.weight      | Block 18 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  170 | blk.18.attn_v.weight      | Block 18 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  171 | blk.18.ffn_down.weight    | Block 18 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  172 | blk.18.ffn_gate.weight    | Block 18 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  173 | blk.18.ffn_norm.weight    | Block 18 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  174 | blk.18.ffn_up.weight      | Block 18 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.18: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  175 | blk.19.attn_k.weight      | Block 19 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  176 | blk.19.attn_norm.weight   | Block 19 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  177 | blk.19.attn_output.weight | Block 19 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  178 | blk.19.attn_q.weight      | Block 19 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  179 | blk.19.attn_v.weight      | Block 19 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  180 | blk.19.ffn_down.weight    | Block 19 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  181 | blk.19.ffn_gate.weight    | Block 19 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  182 | blk.19.ffn_norm.weight    | Block 19 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  183 | blk.19.ffn_up.weight      | Block 19 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.19: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  184 | blk.20.attn_k.weight      | Block 20 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  185 | blk.20.attn_norm.weight   | Block 20 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  186 | blk.20.attn_output.weight | Block 20 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  187 | blk.20.attn_q.weight      | Block 20 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  188 | blk.20.attn_v.weight      | Block 20 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  189 | blk.20.ffn_down.weight    | Block 20 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  190 | blk.20.ffn_gate.weight    | Block 20 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  191 | blk.20.ffn_norm.weight    | Block 20 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  192 | blk.20.ffn_up.weight      | Block 20 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.20: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  193 | blk.21.attn_k.weight      | Block 21 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  194 | blk.21.attn_norm.weight   | Block 21 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  195 | blk.21.attn_output.weight | Block 21 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  196 | blk.21.attn_q.weight      | Block 21 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  197 | blk.21.attn_v.weight      | Block 21 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  198 | blk.21.ffn_down.weight    | Block 21 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  199 | blk.21.ffn_gate.weight    | Block 21 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  200 | blk.21.ffn_norm.weight    | Block 21 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  201 | blk.21.ffn_up.weight      | Block 21 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.21: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  202 | blk.22.attn_k.weight      | Block 22 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  203 | blk.22.attn_norm.weight   | Block 22 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  204 | blk.22.attn_output.weight | Block 22 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  205 | blk.22.attn_q.weight      | Block 22 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  206 | blk.22.attn_v.weight      | Block 22 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  207 | blk.22.ffn_down.weight    | Block 22 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  208 | blk.22.ffn_gate.weight    | Block 22 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  209 | blk.22.ffn_norm.weight    | Block 22 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  210 | blk.22.ffn_up.weight      | Block 22 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.22: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  211 | blk.23.attn_k.weight      | Block 23 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  212 | blk.23.attn_norm.weight   | Block 23 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  213 | blk.23.attn_output.weight | Block 23 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  214 | blk.23.attn_q.weight      | Block 23 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  215 | blk.23.attn_v.weight      | Block 23 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  216 | blk.23.ffn_down.weight    | Block 23 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  217 | blk.23.ffn_gate.weight    | Block 23 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  218 | blk.23.ffn_norm.weight    | Block 23 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  219 | blk.23.ffn_up.weight      | Block 23 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.23: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  220 | blk.24.attn_k.weight      | Block 24 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  221 | blk.24.attn_norm.weight   | Block 24 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  222 | blk.24.attn_output.weight | Block 24 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  223 | blk.24.attn_q.weight      | Block 24 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  224 | blk.24.attn_v.weight      | Block 24 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  225 | blk.24.ffn_down.weight    | Block 24 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  226 | blk.24.ffn_gate.weight    | Block 24 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  227 | blk.24.ffn_norm.weight    | Block 24 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  228 | blk.24.ffn_up.weight      | Block 24 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.24: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  229 | blk.25.attn_k.weight      | Block 25 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  230 | blk.25.attn_norm.weight   | Block 25 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  231 | blk.25.attn_output.weight | Block 25 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  232 | blk.25.attn_q.weight      | Block 25 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  233 | blk.25.attn_v.weight      | Block 25 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  234 | blk.25.ffn_down.weight    | Block 25 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  235 | blk.25.ffn_gate.weight    | Block 25 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  236 | blk.25.ffn_norm.weight    | Block 25 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  237 | blk.25.ffn_up.weight      | Block 25 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.25: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  238 | blk.26.attn_k.weight      | Block 26 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  239 | blk.26.attn_norm.weight   | Block 26 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  240 | blk.26.attn_output.weight | Block 26 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  241 | blk.26.attn_q.weight      | Block 26 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  242 | blk.26.attn_v.weight      | Block 26 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  243 | blk.26.ffn_down.weight    | Block 26 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  244 | blk.26.ffn_gate.weight    | Block 26 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  245 | blk.26.ffn_norm.weight    | Block 26 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  246 | blk.26.ffn_up.weight      | Block 26 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.26: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  247 | blk.27.attn_k.weight      | Block 27 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  248 | blk.27.attn_norm.weight   | Block 27 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  249 | blk.27.attn_output.weight | Block 27 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  250 | blk.27.attn_q.weight      | Block 27 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  251 | blk.27.attn_v.weight      | Block 27 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  252 | blk.27.ffn_down.weight    | Block 27 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  253 | blk.27.ffn_gate.weight    | Block 27 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  254 | blk.27.ffn_norm.weight    | Block 27 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  255 | blk.27.ffn_up.weight      | Block 27 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.27: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  256 | blk.28.attn_k.weight      | Block 28 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  257 | blk.28.attn_norm.weight   | Block 28 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  258 | blk.28.attn_output.weight | Block 28 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  259 | blk.28.attn_q.weight      | Block 28 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  260 | blk.28.attn_v.weight      | Block 28 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  261 | blk.28.ffn_down.weight    | Block 28 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  262 | blk.28.ffn_gate.weight    | Block 28 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  263 | blk.28.ffn_norm.weight    | Block 28 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  264 | blk.28.ffn_up.weight      | Block 28 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.28: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  265 | blk.29.attn_k.weight      | Block 29 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  266 | blk.29.attn_norm.weight   | Block 29 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  267 | blk.29.attn_output.weight | Block 29 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  268 | blk.29.attn_q.weight      | Block 29 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  269 | blk.29.attn_v.weight      | Block 29 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  270 | blk.29.ffn_down.weight    | Block 29 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  271 | blk.29.ffn_gate.weight    | Block 29 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  272 | blk.29.ffn_norm.weight    | Block 29 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  273 | blk.29.ffn_up.weight      | Block 29 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.29: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  274 | blk.30.attn_k.weight      | Block 30 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  275 | blk.30.attn_norm.weight   | Block 30 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  276 | blk.30.attn_output.weight | Block 30 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  277 | blk.30.attn_q.weight      | Block 30 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  278 | blk.30.attn_v.weight      | Block 30 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  279 | blk.30.ffn_down.weight    | Block 30 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  280 | blk.30.ffn_gate.weight    | Block 30 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  281 | blk.30.ffn_norm.weight    | Block 30 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  282 | blk.30.ffn_up.weight      | Block 30 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.30: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  283 | blk.31.attn_k.weight      | Block 31 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q4_K |
+|  284 | blk.31.attn_norm.weight   | Block 31 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  285 | blk.31.attn_output.weight | Block 31 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  286 | blk.31.attn_q.weight      | Block 31 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q4_K |
+|  287 | blk.31.attn_v.weight      | Block 31 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  288 | blk.31.ffn_down.weight    | Block 31 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q6_K |
+|  289 | blk.31.ffn_gate.weight    | Block 31 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  290 | blk.31.ffn_norm.weight    | Block 31 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  291 | blk.31.ffn_up.weight      | Block 31 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.31: (~218M) 218112000
+- Percentage of total elements: 2.72%

scores/Llama-Guard-3-8B-Q6_K.md ADDED Viewed

	@@ -0,0 +1,978 @@

+# Llama-Guard-3-8B-Q6_K.gguf - GGUF Internal File Dump
+- Endian: LITTLE endian
+## Key Value Metadata Store
+There are 39 key-value pairs in this file
+| POS | TYPE     |  Count | Key                                    | Value                                                               |
+|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
+|   1 | UINT32   |      1 | GGUF.version                           | 3                                                                   |
+|   2 | UINT64   |      1 | GGUF.tensor_count                      | 292                                                                 |
+|   3 | UINT64   |      1 | GGUF.kv_count                          | 36                                                                  |
+|   4 | STRING   |      1 | general.architecture                   | `llama`                                                             |
+|   5 | STRING   |      1 | general.type                           | `model`                                                             |
+|   6 | STRING   |      1 | general.name                           | `Llama Guard 3 8B`                                                  |
+|   7 | STRING   |      1 | general.basename                       | `Llama-Guard-3`                                                     |
+|   8 | STRING   |      1 | general.size_label                     | `8B`                                                                |
+|   9 | STRING   |      1 | general.license                        | `llama3.1`                                                          |
+|  10 | UINT32   |      1 | general.base_model.count               | 1                                                                   |
+|  11 | STRING   |      1 | general.base_model.0.name              | `Meta Llama 3.1 8B`                                                 |
+|  12 | STRING   |      1 | general.base_model.0.organization      | `Meta Llama`                                                        |
+|  13 | STRING   |      1 | general.base_model.0.repo_url          | `https://huggingface.co/meta-llama/Meta-Llama-3.1-8B`               |
+|  14 | [STRING] |      6 | general.tags                           | [ `facebook`, `meta`, `pytorch`, `llama`, `llama-3`, ... ]          |
+|  15 | [STRING] |      1 | general.languages                      | [ `en` ]                                                            |
+|  16 | UINT32   |      1 | llama.block_count                      | 32                                                                  |
+|  17 | UINT32   |      1 | llama.context_length                   | 131072                                                              |
+|  18 | UINT32   |      1 | llama.embedding_length                 | 4096                                                                |
+|  19 | UINT32   |      1 | llama.feed_forward_length              | 14336                                                               |
+|  20 | UINT32   |      1 | llama.attention.head_count             | 32                                                                  |
+|  21 | UINT32   |      1 | llama.attention.head_count_kv          | 8                                                                   |
+|  22 | FLOAT32  |      1 | llama.rope.freq_base                   | 500000.0                                                            |
+|  23 | FLOAT32  |      1 | llama.attention.layer_norm_rms_epsilon | 1e-05                                                               |
+|  24 | UINT32   |      1 | llama.vocab_size                       | 128256                                                              |
+|  25 | UINT32   |      1 | llama.rope.dimension_count             | 128                                                                 |
+|  26 | STRING   |      1 | tokenizer.ggml.model                   | `gpt2`                                                              |
+|  27 | STRING   |      1 | tokenizer.ggml.pre                     | `smaug-bpe`                                                         |
+|  28 | [STRING] | 128256 | tokenizer.ggml.tokens                  | [ `!`, `"`, `#`, `$`, `%`, ... ]                                    |
+|  29 | [INT32]  | 128256 | tokenizer.ggml.token_type              | [ 1, 1, 1, 1, 1, 1, 1, ... ]                                        |
+|  30 | [STRING] | 280147 | tokenizer.ggml.merges                  | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]                    |
+|  31 | UINT32   |      1 | tokenizer.ggml.bos_token_id            | 128000                                                              |
+|  32 | UINT32   |      1 | tokenizer.ggml.eos_token_id            | 128009                                                              |
+|  33 | STRING   |      1 | tokenizer.chat_template                | `{% if messages|length % 2 == 0`...`assistant<|end_header_id|>" }}` |
+|  34 | UINT32   |      1 | general.quantization_version           | 2                                                                   |
+|  35 | UINT32   |      1 | general.file_type                      | 18                                                                  |
+|  36 | STRING   |      1 | quantize.imatrix.file                  | `./imatrix/imatrix-Llama-Guard-3-8B-small.dat`                      |
+|  37 | STRING   |      1 | quantize.imatrix.dataset               | `../../datasets/imatrix/calibration_eur_small.txt`                  |
+|  38 | INT32    |      1 | quantize.imatrix.entries_count         | 224                                                                 |
+|  39 | INT32    |      1 | quantize.imatrix.chunks_count          | 962                                                                 |
+## Tensors Overview ~8B Elements
+Total number of elements in all tensors: 8030261312 Elements
+- [Llama-Guard-3-8B-Q6\_K.gguf - GGUF Internal File Dump](#llama-guard-3-8b-q6_kgguf---gguf-internal-file-dump)
+  - [Key Value Metadata Store](#key-value-metadata-store)
+  - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
+    - [Tensor Data Offset](#tensor-data-offset)
+    - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
+    - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
+    - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
+    - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
+    - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
+    - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
+    - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
+    - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
+    - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
+    - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
+    - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
+    - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
+    - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
+    - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
+    - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
+    - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
+    - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
+    - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
+    - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
+    - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
+    - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
+    - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
+    - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
+    - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
+    - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
+    - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
+    - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
+    - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
+    - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
+    - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
+    - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
+    - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
+    - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
+### Tensor Data Offset
+This table contains the offset and data segment relative to start of file
+| T_ID | Tensor Layer Name         |  Data Offset (B) |    Data Size (B) |
+|-----:|:--------------------------|-----------------:|-----------------:|
+|    0 | output.weight             |         0x779880 |       0x19afa000 |
+|    1 | output_norm.weight        |       0x1a273880 |           0x4000 |
+|    2 | rope_freqs.weight         |       0x1a277880 |            0x100 |
+|    3 | token_embd.weight         |       0x1a277980 |        0xd746000 |
+|    4 | blk.0.attn_k.weight       |       0x279bd980 |         0x2c0000 |
+|    5 | blk.0.attn_norm.weight    |       0x27c7d980 |           0x4000 |
+|    6 | blk.0.attn_output.weight  |       0x27c81980 |         0xd20000 |
+|    7 | blk.0.attn_q.weight       |       0x289a1980 |         0xb00000 |
+|    8 | blk.0.attn_v.weight       |       0x294a1980 |         0x348000 |
+|    9 | blk.0.ffn_down.weight     |       0x297e9980 |        0x3b80000 |
+|   10 | blk.0.ffn_gate.weight     |       0x2d369980 |        0x2680000 |
+|   11 | blk.0.ffn_norm.weight     |       0x2f9e9980 |           0x4000 |
+|   12 | blk.0.ffn_up.weight       |       0x2f9ed980 |        0x2680000 |
+|   13 | blk.1.attn_k.weight       |       0x3206d980 |         0x2c0000 |
+|   14 | blk.1.attn_norm.weight    |       0x3232d980 |           0x4000 |
+|   15 | blk.1.attn_output.weight  |       0x32331980 |         0xd20000 |
+|   16 | blk.1.attn_q.weight       |       0x33051980 |         0xb00000 |
+|   17 | blk.1.attn_v.weight       |       0x33b51980 |         0x348000 |
+|   18 | blk.1.ffn_down.weight     |       0x33e99980 |        0x3b80000 |
+|   19 | blk.1.ffn_gate.weight     |       0x37a19980 |        0x2680000 |
+|   20 | blk.1.ffn_norm.weight     |       0x3a099980 |           0x4000 |
+|   21 | blk.1.ffn_up.weight       |       0x3a09d980 |        0x2680000 |
+|   22 | blk.2.attn_k.weight       |       0x3c71d980 |         0x2c0000 |
+|   23 | blk.2.attn_norm.weight    |       0x3c9dd980 |           0x4000 |
+|   24 | blk.2.attn_output.weight  |       0x3c9e1980 |         0xd20000 |
+|   25 | blk.2.attn_q.weight       |       0x3d701980 |         0xb00000 |
+|   26 | blk.2.attn_v.weight       |       0x3e201980 |         0x348000 |
+|   27 | blk.2.ffn_down.weight     |       0x3e549980 |        0x3b80000 |
+|   28 | blk.2.ffn_gate.weight     |       0x420c9980 |        0x2680000 |
+|   29 | blk.2.ffn_norm.weight     |       0x44749980 |           0x4000 |
+|   30 | blk.2.ffn_up.weight       |       0x4474d980 |        0x2680000 |
+|   31 | blk.3.attn_k.weight       |       0x46dcd980 |         0x2c0000 |
+|   32 | blk.3.attn_norm.weight    |       0x4708d980 |           0x4000 |
+|   33 | blk.3.attn_output.weight  |       0x47091980 |         0xd20000 |
+|   34 | blk.3.attn_q.weight       |       0x47db1980 |         0xb00000 |
+|   35 | blk.3.attn_v.weight       |       0x488b1980 |         0x348000 |
+|   36 | blk.3.ffn_down.weight     |       0x48bf9980 |        0x3b80000 |
+|   37 | blk.3.ffn_gate.weight     |       0x4c779980 |        0x2680000 |
+|   38 | blk.3.ffn_norm.weight     |       0x4edf9980 |           0x4000 |
+|   39 | blk.3.ffn_up.weight       |       0x4edfd980 |        0x2680000 |
+|   40 | blk.4.attn_k.weight       |       0x5147d980 |         0x2c0000 |
+|   41 | blk.4.attn_norm.weight    |       0x5173d980 |           0x4000 |
+|   42 | blk.4.attn_output.weight  |       0x51741980 |         0xd20000 |
+|   43 | blk.4.attn_q.weight       |       0x52461980 |         0xb00000 |
+|   44 | blk.4.attn_v.weight       |       0x52f61980 |         0x348000 |
+|   45 | blk.4.ffn_down.weight     |       0x532a9980 |        0x3b80000 |
+|   46 | blk.4.ffn_gate.weight     |       0x56e29980 |        0x2680000 |
+|   47 | blk.4.ffn_norm.weight     |       0x594a9980 |           0x4000 |
+|   48 | blk.4.ffn_up.weight       |       0x594ad980 |        0x2680000 |
+|   49 | blk.5.attn_k.weight       |       0x5bb2d980 |         0x2c0000 |
+|   50 | blk.5.attn_norm.weight    |       0x5bded980 |           0x4000 |
+|   51 | blk.5.attn_output.weight  |       0x5bdf1980 |         0xd20000 |
+|   52 | blk.5.attn_q.weight       |       0x5cb11980 |         0xb00000 |
+|   53 | blk.5.attn_v.weight       |       0x5d611980 |         0x348000 |
+|   54 | blk.5.ffn_down.weight     |       0x5d959980 |        0x3b80000 |
+|   55 | blk.5.ffn_gate.weight     |       0x614d9980 |        0x2680000 |
+|   56 | blk.5.ffn_norm.weight     |       0x63b59980 |           0x4000 |
+|   57 | blk.5.ffn_up.weight       |       0x63b5d980 |        0x2680000 |
+|   58 | blk.6.attn_k.weight       |       0x661dd980 |         0x2c0000 |
+|   59 | blk.6.attn_norm.weight    |       0x6649d980 |           0x4000 |
+|   60 | blk.6.attn_output.weight  |       0x664a1980 |         0xd20000 |
+|   61 | blk.6.attn_q.weight       |       0x671c1980 |         0xb00000 |
+|   62 | blk.6.attn_v.weight       |       0x67cc1980 |         0x348000 |
+|   63 | blk.6.ffn_down.weight     |       0x68009980 |        0x3b80000 |
+|   64 | blk.6.ffn_gate.weight     |       0x6bb89980 |        0x2680000 |
+|   65 | blk.6.ffn_norm.weight     |       0x6e209980 |           0x4000 |
+|   66 | blk.6.ffn_up.weight       |       0x6e20d980 |        0x2680000 |
+|   67 | blk.7.attn_k.weight       |       0x7088d980 |         0x2c0000 |
+|   68 | blk.7.attn_norm.weight    |       0x70b4d980 |           0x4000 |
+|   69 | blk.7.attn_output.weight  |       0x70b51980 |         0xd20000 |
+|   70 | blk.7.attn_q.weight       |       0x71871980 |         0xb00000 |
+|   71 | blk.7.attn_v.weight       |       0x72371980 |         0x348000 |
+|   72 | blk.7.ffn_down.weight     |       0x726b9980 |        0x3b80000 |
+|   73 | blk.7.ffn_gate.weight     |       0x76239980 |        0x2680000 |
+|   74 | blk.7.ffn_norm.weight     |       0x788b9980 |           0x4000 |
+|   75 | blk.7.ffn_up.weight       |       0x788bd980 |        0x2680000 |
+|   76 | blk.8.attn_k.weight       |       0x7af3d980 |         0x2c0000 |
+|   77 | blk.8.attn_norm.weight    |       0x7b1fd980 |           0x4000 |
+|   78 | blk.8.attn_output.weight  |       0x7b201980 |         0xd20000 |
+|   79 | blk.8.attn_q.weight       |       0x7bf21980 |         0xb00000 |
+|   80 | blk.8.attn_v.weight       |       0x7ca21980 |         0x348000 |
+|   81 | blk.8.ffn_down.weight     |       0x7cd69980 |        0x3b80000 |
+|   82 | blk.8.ffn_gate.weight     |       0x808e9980 |        0x2680000 |
+|   83 | blk.8.ffn_norm.weight     |       0x82f69980 |           0x4000 |
+|   84 | blk.8.ffn_up.weight       |       0x82f6d980 |        0x2680000 |
+|   85 | blk.9.attn_k.weight       |       0x855ed980 |         0x2c0000 |
+|   86 | blk.9.attn_norm.weight    |       0x858ad980 |           0x4000 |
+|   87 | blk.9.attn_output.weight  |       0x858b1980 |         0xd20000 |
+|   88 | blk.9.attn_q.weight       |       0x865d1980 |         0xb00000 |
+|   89 | blk.9.attn_v.weight       |       0x870d1980 |         0x348000 |
+|   90 | blk.9.ffn_down.weight     |       0x87419980 |        0x3b80000 |
+|   91 | blk.9.ffn_gate.weight     |       0x8af99980 |        0x2680000 |
+|   92 | blk.9.ffn_norm.weight     |       0x8d619980 |           0x4000 |
+|   93 | blk.9.ffn_up.weight       |       0x8d61d980 |        0x2680000 |
+|   94 | blk.10.attn_k.weight      |       0x8fc9d980 |         0x2c0000 |
+|   95 | blk.10.attn_norm.weight   |       0x8ff5d980 |           0x4000 |
+|   96 | blk.10.attn_output.weight |       0x8ff61980 |         0xd20000 |
+|   97 | blk.10.attn_q.weight      |       0x90c81980 |         0xb00000 |
+|   98 | blk.10.attn_v.weight      |       0x91781980 |         0x348000 |
+|   99 | blk.10.ffn_down.weight    |       0x91ac9980 |        0x3b80000 |
+|  100 | blk.10.ffn_gate.weight    |       0x95649980 |        0x2680000 |
+|  101 | blk.10.ffn_norm.weight    |       0x97cc9980 |           0x4000 |
+|  102 | blk.10.ffn_up.weight      |       0x97ccd980 |        0x2680000 |
+|  103 | blk.11.attn_k.weight      |       0x9a34d980 |         0x2c0000 |
+|  104 | blk.11.attn_norm.weight   |       0x9a60d980 |           0x4000 |
+|  105 | blk.11.attn_output.weight |       0x9a611980 |         0xd20000 |
+|  106 | blk.11.attn_q.weight      |       0x9b331980 |         0xb00000 |
+|  107 | blk.11.attn_v.weight      |       0x9be31980 |         0x348000 |
+|  108 | blk.11.ffn_down.weight    |       0x9c179980 |        0x3b80000 |
+|  109 | blk.11.ffn_gate.weight    |       0x9fcf9980 |        0x2680000 |
+|  110 | blk.11.ffn_norm.weight    |       0xa2379980 |           0x4000 |
+|  111 | blk.11.ffn_up.weight      |       0xa237d980 |        0x2680000 |
+|  112 | blk.12.attn_k.weight      |       0xa49fd980 |         0x2c0000 |
+|  113 | blk.12.attn_norm.weight   |       0xa4cbd980 |           0x4000 |
+|  114 | blk.12.attn_output.weight |       0xa4cc1980 |         0xd20000 |
+|  115 | blk.12.attn_q.weight      |       0xa59e1980 |         0xb00000 |
+|  116 | blk.12.attn_v.weight      |       0xa64e1980 |         0x348000 |
+|  117 | blk.12.ffn_down.weight    |       0xa6829980 |        0x3b80000 |
+|  118 | blk.12.ffn_gate.weight    |       0xaa3a9980 |        0x2680000 |
+|  119 | blk.12.ffn_norm.weight    |       0xaca29980 |           0x4000 |
+|  120 | blk.12.ffn_up.weight      |       0xaca2d980 |        0x2680000 |
+|  121 | blk.13.attn_k.weight      |       0xaf0ad980 |         0x348000 |
+|  122 | blk.13.attn_norm.weight   |       0xaf3f5980 |           0x4000 |
+|  123 | blk.13.attn_output.weight |       0xaf3f9980 |         0xd20000 |
+|  124 | blk.13.attn_q.weight      |       0xb0119980 |         0xd20000 |
+|  125 | blk.13.attn_v.weight      |       0xb0e39980 |         0x440000 |
+|  126 | blk.13.ffn_down.weight    |       0xb1279980 |        0x3b80000 |
+|  127 | blk.13.ffn_gate.weight    |       0xb4df9980 |        0x2680000 |
+|  128 | blk.13.ffn_norm.weight    |       0xb7479980 |           0x4000 |
+|  129 | blk.13.ffn_up.weight      |       0xb747d980 |        0x2680000 |
+|  130 | blk.14.attn_k.weight      |       0xb9afd980 |         0x348000 |
+|  131 | blk.14.attn_norm.weight   |       0xb9e45980 |           0x4000 |
+|  132 | blk.14.attn_output.weight |       0xb9e49980 |         0xd20000 |
+|  133 | blk.14.attn_q.weight      |       0xbab69980 |         0xd20000 |
+|  134 | blk.14.attn_v.weight      |       0xbb889980 |         0x440000 |
+|  135 | blk.14.ffn_down.weight    |       0xbbcc9980 |        0x3b80000 |
+|  136 | blk.14.ffn_gate.weight    |       0xbf849980 |        0x2680000 |
+|  137 | blk.14.ffn_norm.weight    |       0xc1ec9980 |           0x4000 |
+|  138 | blk.14.ffn_up.weight      |       0xc1ecd980 |        0x2680000 |
+|  139 | blk.15.attn_k.weight      |       0xc454d980 |         0x2c0000 |
+|  140 | blk.15.attn_norm.weight   |       0xc480d980 |           0x4000 |
+|  141 | blk.15.attn_output.weight |       0xc4811980 |         0xd20000 |
+|  142 | blk.15.attn_q.weight      |       0xc5531980 |         0xb00000 |
+|  143 | blk.15.attn_v.weight      |       0xc6031980 |         0x348000 |
+|  144 | blk.15.ffn_down.weight    |       0xc6379980 |        0x3b80000 |
+|  145 | blk.15.ffn_gate.weight    |       0xc9ef9980 |        0x2680000 |
+|  146 | blk.15.ffn_norm.weight    |       0xcc579980 |           0x4000 |
+|  147 | blk.15.ffn_up.weight      |       0xcc57d980 |        0x2680000 |
+|  148 | blk.16.attn_k.weight      |       0xcebfd980 |         0x348000 |
+|  149 | blk.16.attn_norm.weight   |       0xcef45980 |           0x4000 |
+|  150 | blk.16.attn_output.weight |       0xcef49980 |         0xd20000 |
+|  151 | blk.16.attn_q.weight      |       0xcfc69980 |         0xd20000 |
+|  152 | blk.16.attn_v.weight      |       0xd0989980 |         0x440000 |
+|  153 | blk.16.ffn_down.weight    |       0xd0dc9980 |        0x3b80000 |
+|  154 | blk.16.ffn_gate.weight    |       0xd4949980 |        0x2df0000 |
+|  155 | blk.16.ffn_norm.weight    |       0xd7739980 |           0x4000 |
+|  156 | blk.16.ffn_up.weight      |       0xd773d980 |        0x2df0000 |
+|  157 | blk.17.attn_k.weight      |       0xda52d980 |         0x2c0000 |
+|  158 | blk.17.attn_norm.weight   |       0xda7ed980 |           0x4000 |
+|  159 | blk.17.attn_output.weight |       0xda7f1980 |         0xd20000 |
+|  160 | blk.17.attn_q.weight      |       0xdb511980 |         0xb00000 |
+|  161 | blk.17.attn_v.weight      |       0xdc011980 |         0x348000 |
+|  162 | blk.17.ffn_down.weight    |       0xdc359980 |        0x3b80000 |
+|  163 | blk.17.ffn_gate.weight    |       0xdfed9980 |        0x2df0000 |
+|  164 | blk.17.ffn_norm.weight    |       0xe2cc9980 |           0x4000 |
+|  165 | blk.17.ffn_up.weight      |       0xe2ccd980 |        0x2df0000 |
+|  166 | blk.18.attn_k.weight      |       0xe5abd980 |         0x348000 |
+|  167 | blk.18.attn_norm.weight   |       0xe5e05980 |           0x4000 |
+|  168 | blk.18.attn_output.weight |       0xe5e09980 |         0xd20000 |
+|  169 | blk.18.attn_q.weight      |       0xe6b29980 |         0xd20000 |
+|  170 | blk.18.attn_v.weight      |       0xe7849980 |         0x440000 |
+|  171 | blk.18.ffn_down.weight    |       0xe7c89980 |        0x3b80000 |
+|  172 | blk.18.ffn_gate.weight    |       0xeb809980 |        0x2df0000 |
+|  173 | blk.18.ffn_norm.weight    |       0xee5f9980 |           0x4000 |
+|  174 | blk.18.ffn_up.weight      |       0xee5fd980 |        0x2df0000 |
+|  175 | blk.19.attn_k.weight      |       0xf13ed980 |         0x348000 |
+|  176 | blk.19.attn_norm.weight   |       0xf1735980 |           0x4000 |
+|  177 | blk.19.attn_output.weight |       0xf1739980 |         0xd20000 |
+|  178 | blk.19.attn_q.weight      |       0xf2459980 |         0xd20000 |
+|  179 | blk.19.attn_v.weight      |       0xf3179980 |         0x440000 |
+|  180 | blk.19.ffn_down.weight    |       0xf35b9980 |        0x3b80000 |
+|  181 | blk.19.ffn_gate.weight    |       0xf7139980 |        0x2df0000 |
+|  182 | blk.19.ffn_norm.weight    |       0xf9f29980 |           0x4000 |
+|  183 | blk.19.ffn_up.weight      |       0xf9f2d980 |        0x2df0000 |
+|  184 | blk.20.attn_k.weight      |       0xfcd1d980 |         0x348000 |
+|  185 | blk.20.attn_norm.weight   |       0xfd065980 |           0x4000 |
+|  186 | blk.20.attn_output.weight |       0xfd069980 |         0xd20000 |
+|  187 | blk.20.attn_q.weight      |       0xfdd89980 |         0xd20000 |
+|  188 | blk.20.attn_v.weight      |       0xfeaa9980 |         0x440000 |
+|  189 | blk.20.ffn_down.weight    |       0xfeee9980 |        0x3b80000 |
+|  190 | blk.20.ffn_gate.weight    |      0x102a69980 |        0x2df0000 |
+|  191 | blk.20.ffn_norm.weight    |      0x105859980 |           0x4000 |
+|  192 | blk.20.ffn_up.weight      |      0x10585d980 |        0x2df0000 |
+|  193 | blk.21.attn_k.weight      |      0x10864d980 |         0x348000 |
+|  194 | blk.21.attn_norm.weight   |      0x108995980 |           0x4000 |
+|  195 | blk.21.attn_output.weight |      0x108999980 |         0xd20000 |
+|  196 | blk.21.attn_q.weight      |      0x1096b9980 |         0xd20000 |
+|  197 | blk.21.attn_v.weight      |      0x10a3d9980 |         0x440000 |
+|  198 | blk.21.ffn_down.weight    |      0x10a819980 |        0x3b80000 |
+|  199 | blk.21.ffn_gate.weight    |      0x10e399980 |        0x2df0000 |
+|  200 | blk.21.ffn_norm.weight    |      0x111189980 |           0x4000 |
+|  201 | blk.21.ffn_up.weight      |      0x11118d980 |        0x2df0000 |
+|  202 | blk.22.attn_k.weight      |      0x113f7d980 |         0x348000 |
+|  203 | blk.22.attn_norm.weight   |      0x1142c5980 |           0x4000 |
+|  204 | blk.22.attn_output.weight |      0x1142c9980 |         0xd20000 |
+|  205 | blk.22.attn_q.weight      |      0x114fe9980 |         0xd20000 |
+|  206 | blk.22.attn_v.weight      |      0x115d09980 |         0x440000 |
+|  207 | blk.22.ffn_down.weight    |      0x116149980 |        0x3b80000 |
+|  208 | blk.22.ffn_gate.weight    |      0x119cc9980 |        0x2df0000 |
+|  209 | blk.22.ffn_norm.weight    |      0x11cab9980 |           0x4000 |
+|  210 | blk.22.ffn_up.weight      |      0x11cabd980 |        0x2df0000 |
+|  211 | blk.23.attn_k.weight      |      0x11f8ad980 |         0x348000 |
+|  212 | blk.23.attn_norm.weight   |      0x11fbf5980 |           0x4000 |
+|  213 | blk.23.attn_output.weight |      0x11fbf9980 |         0xd20000 |
+|  214 | blk.23.attn_q.weight      |      0x120919980 |         0xd20000 |
+|  215 | blk.23.attn_v.weight      |      0x121639980 |         0x440000 |
+|  216 | blk.23.ffn_down.weight    |      0x121a79980 |        0x3b80000 |
+|  217 | blk.23.ffn_gate.weight    |      0x1255f9980 |        0x2df0000 |
+|  218 | blk.23.ffn_norm.weight    |      0x1283e9980 |           0x4000 |
+|  219 | blk.23.ffn_up.weight      |      0x1283ed980 |        0x2df0000 |
+|  220 | blk.24.attn_k.weight      |      0x12b1dd980 |         0x348000 |
+|  221 | blk.24.attn_norm.weight   |      0x12b525980 |           0x4000 |
+|  222 | blk.24.attn_output.weight |      0x12b529980 |         0xd20000 |
+|  223 | blk.24.attn_q.weight      |      0x12c249980 |         0xd20000 |
+|  224 | blk.24.attn_v.weight      |      0x12cf69980 |         0x440000 |
+|  225 | blk.24.ffn_down.weight    |      0x12d3a9980 |        0x3b80000 |
+|  226 | blk.24.ffn_gate.weight    |      0x130f29980 |        0x2df0000 |
+|  227 | blk.24.ffn_norm.weight    |      0x133d19980 |           0x4000 |
+|  228 | blk.24.ffn_up.weight      |      0x133d1d980 |        0x2df0000 |
+|  229 | blk.25.attn_k.weight      |      0x136b0d980 |         0x348000 |
+|  230 | blk.25.attn_norm.weight   |      0x136e55980 |           0x4000 |
+|  231 | blk.25.attn_output.weight |      0x136e59980 |         0xd20000 |
+|  232 | blk.25.attn_q.weight      |      0x137b79980 |         0xd20000 |
+|  233 | blk.25.attn_v.weight      |      0x138899980 |         0x440000 |
+|  234 | blk.25.ffn_down.weight    |      0x138cd9980 |        0x3b80000 |
+|  235 | blk.25.ffn_gate.weight    |      0x13c859980 |        0x2df0000 |
+|  236 | blk.25.ffn_norm.weight    |      0x13f649980 |           0x4000 |
+|  237 | blk.25.ffn_up.weight      |      0x13f64d980 |        0x2df0000 |
+|  238 | blk.26.attn_k.weight      |      0x14243d980 |         0x348000 |
+|  239 | blk.26.attn_norm.weight   |      0x142785980 |           0x4000 |
+|  240 | blk.26.attn_output.weight |      0x142789980 |         0xd20000 |
+|  241 | blk.26.attn_q.weight      |      0x1434a9980 |         0xd20000 |
+|  242 | blk.26.attn_v.weight      |      0x1441c9980 |         0x440000 |
+|  243 | blk.26.ffn_down.weight    |      0x144609980 |        0x3b80000 |
+|  244 | blk.26.ffn_gate.weight    |      0x148189980 |        0x2df0000 |
+|  245 | blk.26.ffn_norm.weight    |      0x14af79980 |           0x4000 |
+|  246 | blk.26.ffn_up.weight      |      0x14af7d980 |        0x2df0000 |
+|  247 | blk.27.attn_k.weight      |      0x14dd6d980 |         0x348000 |
+|  248 | blk.27.attn_norm.weight   |      0x14e0b5980 |           0x4000 |
+|  249 | blk.27.attn_output.weight |      0x14e0b9980 |         0xd20000 |
+|  250 | blk.27.attn_q.weight      |      0x14edd9980 |         0xd20000 |
+|  251 | blk.27.attn_v.weight      |      0x14faf9980 |         0x440000 |
+|  252 | blk.27.ffn_down.weight    |      0x14ff39980 |        0x3b80000 |
+|  253 | blk.27.ffn_gate.weight    |      0x153ab9980 |        0x2df0000 |
+|  254 | blk.27.ffn_norm.weight    |      0x1568a9980 |           0x4000 |
+|  255 | blk.27.ffn_up.weight      |      0x1568ad980 |        0x2df0000 |
+|  256 | blk.28.attn_k.weight      |      0x15969d980 |         0x348000 |
+|  257 | blk.28.attn_norm.weight   |      0x1599e5980 |           0x4000 |
+|  258 | blk.28.attn_output.weight |      0x1599e9980 |         0xd20000 |
+|  259 | blk.28.attn_q.weight      |      0x15a709980 |         0xd20000 |
+|  260 | blk.28.attn_v.weight      |      0x15b429980 |         0x440000 |
+|  261 | blk.28.ffn_down.weight    |      0x15b869980 |        0x3b80000 |
+|  262 | blk.28.ffn_gate.weight    |      0x15f3e9980 |        0x2df0000 |
+|  263 | blk.28.ffn_norm.weight    |      0x1621d9980 |           0x4000 |
+|  264 | blk.28.ffn_up.weight      |      0x1621dd980 |        0x2df0000 |
+|  265 | blk.29.attn_k.weight      |      0x164fcd980 |         0x348000 |
+|  266 | blk.29.attn_norm.weight   |      0x165315980 |           0x4000 |
+|  267 | blk.29.attn_output.weight |      0x165319980 |         0xd20000 |
+|  268 | blk.29.attn_q.weight      |      0x166039980 |         0xd20000 |
+|  269 | blk.29.attn_v.weight      |      0x166d59980 |         0x440000 |
+|  270 | blk.29.ffn_down.weight    |      0x167199980 |        0x3b80000 |
+|  271 | blk.29.ffn_gate.weight    |      0x16ad19980 |        0x2df0000 |
+|  272 | blk.29.ffn_norm.weight    |      0x16db09980 |           0x4000 |
+|  273 | blk.29.ffn_up.weight      |      0x16db0d980 |        0x2df0000 |
+|  274 | blk.30.attn_k.weight      |      0x1708fd980 |         0x348000 |
+|  275 | blk.30.attn_norm.weight   |      0x170c45980 |           0x4000 |
+|  276 | blk.30.attn_output.weight |      0x170c49980 |         0xd20000 |
+|  277 | blk.30.attn_q.weight      |      0x171969980 |         0xd20000 |
+|  278 | blk.30.attn_v.weight      |      0x172689980 |         0x440000 |
+|  279 | blk.30.ffn_down.weight    |      0x172ac9980 |        0x3b80000 |
+|  280 | blk.30.ffn_gate.weight    |      0x176649980 |        0x2df0000 |
+|  281 | blk.30.ffn_norm.weight    |      0x179439980 |           0x4000 |
+|  282 | blk.30.ffn_up.weight      |      0x17943d980 |        0x2df0000 |
+|  283 | blk.31.attn_k.weight      |      0x17c22d980 |         0x2c0000 |
+|  284 | blk.31.attn_norm.weight   |      0x17c4ed980 |           0x4000 |
+|  285 | blk.31.attn_output.weight |      0x17c4f1980 |         0xd20000 |
+|  286 | blk.31.attn_q.weight      |      0x17d211980 |         0xb00000 |
+|  287 | blk.31.attn_v.weight      |      0x17dd11980 |         0x348000 |
+|  288 | blk.31.ffn_down.weight    |      0x17e059980 |        0x3b80000 |
+|  289 | blk.31.ffn_gate.weight    |      0x181bd9980 |        0x2df0000 |
+|  290 | blk.31.ffn_norm.weight    |      0x1849c9980 |           0x4000 |
+|  291 | blk.31.ffn_up.weight      |      0x1849cd980 |        0x2df0000 |
+### <a name="base">Base Tensor Group : ~1B Elements</a>
+| T_ID | Tensor Layer Name  | Human Friendly Tensor Layer Name | Elements          | Shape                 | Type |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
+|    0 | output.weight      | Output (W)                       | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q6_K |
+|    1 | output_norm.weight | Output Normalization (W)         | (  ~4K)      4096 | 4096 x      1 x 1 x 1 | F32  |
+|    2 | rope_freqs.weight  | Rope_Freqs (W)                   | (   64)        64 |   64 x      1 x 1 x 1 | F32  |
+|    3 | token_embd.weight  | Token Embedding (W)              | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q3_K |
+- Total elements in base: ( ~1B) 1050677312
+- Percentage of total elements: 13.08%
+### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|    4 | blk.0.attn_k.weight      | Block 0 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|    5 | blk.0.attn_norm.weight   | Block 0 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|    6 | blk.0.attn_output.weight | Block 0 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|    7 | blk.0.attn_q.weight      | Block 0 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|    8 | blk.0.attn_v.weight      | Block 0 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|    9 | blk.0.ffn_down.weight    | Block 0 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   10 | blk.0.ffn_gate.weight    | Block 0 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|   11 | blk.0.ffn_norm.weight    | Block 0 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   12 | blk.0.ffn_up.weight      | Block 0 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.0: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   13 | blk.1.attn_k.weight      | Block 1 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   14 | blk.1.attn_norm.weight   | Block 1 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   15 | blk.1.attn_output.weight | Block 1 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   16 | blk.1.attn_q.weight      | Block 1 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   17 | blk.1.attn_v.weight      | Block 1 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   18 | blk.1.ffn_down.weight    | Block 1 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   19 | blk.1.ffn_gate.weight    | Block 1 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|   20 | blk.1.ffn_norm.weight    | Block 1 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   21 | blk.1.ffn_up.weight      | Block 1 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.1: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   22 | blk.2.attn_k.weight      | Block 2 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   23 | blk.2.attn_norm.weight   | Block 2 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   24 | blk.2.attn_output.weight | Block 2 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   25 | blk.2.attn_q.weight      | Block 2 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   26 | blk.2.attn_v.weight      | Block 2 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   27 | blk.2.ffn_down.weight    | Block 2 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   28 | blk.2.ffn_gate.weight    | Block 2 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|   29 | blk.2.ffn_norm.weight    | Block 2 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   30 | blk.2.ffn_up.weight      | Block 2 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.2: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   31 | blk.3.attn_k.weight      | Block 3 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   32 | blk.3.attn_norm.weight   | Block 3 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   33 | blk.3.attn_output.weight | Block 3 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   34 | blk.3.attn_q.weight      | Block 3 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   35 | blk.3.attn_v.weight      | Block 3 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   36 | blk.3.ffn_down.weight    | Block 3 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   37 | blk.3.ffn_gate.weight    | Block 3 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|   38 | blk.3.ffn_norm.weight    | Block 3 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   39 | blk.3.ffn_up.weight      | Block 3 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.3: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   40 | blk.4.attn_k.weight      | Block 4 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   41 | blk.4.attn_norm.weight   | Block 4 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   42 | blk.4.attn_output.weight | Block 4 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   43 | blk.4.attn_q.weight      | Block 4 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   44 | blk.4.attn_v.weight      | Block 4 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   45 | blk.4.ffn_down.weight    | Block 4 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   46 | blk.4.ffn_gate.weight    | Block 4 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|   47 | blk.4.ffn_norm.weight    | Block 4 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   48 | blk.4.ffn_up.weight      | Block 4 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.4: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   49 | blk.5.attn_k.weight      | Block 5 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   50 | blk.5.attn_norm.weight   | Block 5 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   51 | blk.5.attn_output.weight | Block 5 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   52 | blk.5.attn_q.weight      | Block 5 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   53 | blk.5.attn_v.weight      | Block 5 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   54 | blk.5.ffn_down.weight    | Block 5 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   55 | blk.5.ffn_gate.weight    | Block 5 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|   56 | blk.5.ffn_norm.weight    | Block 5 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   57 | blk.5.ffn_up.weight      | Block 5 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.5: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   58 | blk.6.attn_k.weight      | Block 6 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   59 | blk.6.attn_norm.weight   | Block 6 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   60 | blk.6.attn_output.weight | Block 6 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   61 | blk.6.attn_q.weight      | Block 6 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   62 | blk.6.attn_v.weight      | Block 6 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   63 | blk.6.ffn_down.weight    | Block 6 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   64 | blk.6.ffn_gate.weight    | Block 6 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|   65 | blk.6.ffn_norm.weight    | Block 6 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   66 | blk.6.ffn_up.weight      | Block 6 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.6: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   67 | blk.7.attn_k.weight      | Block 7 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   68 | blk.7.attn_norm.weight   | Block 7 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   69 | blk.7.attn_output.weight | Block 7 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   70 | blk.7.attn_q.weight      | Block 7 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   71 | blk.7.attn_v.weight      | Block 7 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   72 | blk.7.ffn_down.weight    | Block 7 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   73 | blk.7.ffn_gate.weight    | Block 7 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|   74 | blk.7.ffn_norm.weight    | Block 7 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   75 | blk.7.ffn_up.weight      | Block 7 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.7: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   76 | blk.8.attn_k.weight      | Block 8 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   77 | blk.8.attn_norm.weight   | Block 8 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   78 | blk.8.attn_output.weight | Block 8 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   79 | blk.8.attn_q.weight      | Block 8 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   80 | blk.8.attn_v.weight      | Block 8 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   81 | blk.8.ffn_down.weight    | Block 8 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   82 | blk.8.ffn_gate.weight    | Block 8 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|   83 | blk.8.ffn_norm.weight    | Block 8 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   84 | blk.8.ffn_up.weight      | Block 8 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.8: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   85 | blk.9.attn_k.weight      | Block 9 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   86 | blk.9.attn_norm.weight   | Block 9 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   87 | blk.9.attn_output.weight | Block 9 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   88 | blk.9.attn_q.weight      | Block 9 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   89 | blk.9.attn_v.weight      | Block 9 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   90 | blk.9.ffn_down.weight    | Block 9 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   91 | blk.9.ffn_gate.weight    | Block 9 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|   92 | blk.9.ffn_norm.weight    | Block 9 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   93 | blk.9.ffn_up.weight      | Block 9 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.9: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|   94 | blk.10.attn_k.weight      | Block 10 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|   95 | blk.10.attn_norm.weight   | Block 10 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   96 | blk.10.attn_output.weight | Block 10 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   97 | blk.10.attn_q.weight      | Block 10 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|   98 | blk.10.attn_v.weight      | Block 10 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   99 | blk.10.ffn_down.weight    | Block 10 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  100 | blk.10.ffn_gate.weight    | Block 10 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  101 | blk.10.ffn_norm.weight    | Block 10 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  102 | blk.10.ffn_up.weight      | Block 10 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.10: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  103 | blk.11.attn_k.weight      | Block 11 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  104 | blk.11.attn_norm.weight   | Block 11 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  105 | blk.11.attn_output.weight | Block 11 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  106 | blk.11.attn_q.weight      | Block 11 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  107 | blk.11.attn_v.weight      | Block 11 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  108 | blk.11.ffn_down.weight    | Block 11 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  109 | blk.11.ffn_gate.weight    | Block 11 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  110 | blk.11.ffn_norm.weight    | Block 11 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  111 | blk.11.ffn_up.weight      | Block 11 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.11: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  112 | blk.12.attn_k.weight      | Block 12 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  113 | blk.12.attn_norm.weight   | Block 12 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  114 | blk.12.attn_output.weight | Block 12 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  115 | blk.12.attn_q.weight      | Block 12 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  116 | blk.12.attn_v.weight      | Block 12 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  117 | blk.12.ffn_down.weight    | Block 12 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  118 | blk.12.ffn_gate.weight    | Block 12 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  119 | blk.12.ffn_norm.weight    | Block 12 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  120 | blk.12.ffn_up.weight      | Block 12 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.12: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  121 | blk.13.attn_k.weight      | Block 13 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  122 | blk.13.attn_norm.weight   | Block 13 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  123 | blk.13.attn_output.weight | Block 13 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  124 | blk.13.attn_q.weight      | Block 13 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  125 | blk.13.attn_v.weight      | Block 13 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  126 | blk.13.ffn_down.weight    | Block 13 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  127 | blk.13.ffn_gate.weight    | Block 13 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  128 | blk.13.ffn_norm.weight    | Block 13 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  129 | blk.13.ffn_up.weight      | Block 13 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.13: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  130 | blk.14.attn_k.weight      | Block 14 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  131 | blk.14.attn_norm.weight   | Block 14 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  132 | blk.14.attn_output.weight | Block 14 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  133 | blk.14.attn_q.weight      | Block 14 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  134 | blk.14.attn_v.weight      | Block 14 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  135 | blk.14.ffn_down.weight    | Block 14 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  136 | blk.14.ffn_gate.weight    | Block 14 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  137 | blk.14.ffn_norm.weight    | Block 14 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  138 | blk.14.ffn_up.weight      | Block 14 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.14: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  139 | blk.15.attn_k.weight      | Block 15 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  140 | blk.15.attn_norm.weight   | Block 15 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  141 | blk.15.attn_output.weight | Block 15 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  142 | blk.15.attn_q.weight      | Block 15 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  143 | blk.15.attn_v.weight      | Block 15 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  144 | blk.15.ffn_down.weight    | Block 15 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  145 | blk.15.ffn_gate.weight    | Block 15 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+|  146 | blk.15.ffn_norm.weight    | Block 15 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  147 | blk.15.ffn_up.weight      | Block 15 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q5_K |
+- Total elements in blk.15: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  148 | blk.16.attn_k.weight      | Block 16 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  149 | blk.16.attn_norm.weight   | Block 16 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  150 | blk.16.attn_output.weight | Block 16 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  151 | blk.16.attn_q.weight      | Block 16 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  152 | blk.16.attn_v.weight      | Block 16 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  153 | blk.16.ffn_down.weight    | Block 16 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  154 | blk.16.ffn_gate.weight    | Block 16 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  155 | blk.16.ffn_norm.weight    | Block 16 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  156 | blk.16.ffn_up.weight      | Block 16 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.16: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  157 | blk.17.attn_k.weight      | Block 17 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  158 | blk.17.attn_norm.weight   | Block 17 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  159 | blk.17.attn_output.weight | Block 17 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  160 | blk.17.attn_q.weight      | Block 17 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  161 | blk.17.attn_v.weight      | Block 17 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  162 | blk.17.ffn_down.weight    | Block 17 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  163 | blk.17.ffn_gate.weight    | Block 17 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  164 | blk.17.ffn_norm.weight    | Block 17 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  165 | blk.17.ffn_up.weight      | Block 17 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.17: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  166 | blk.18.attn_k.weight      | Block 18 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  167 | blk.18.attn_norm.weight   | Block 18 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  168 | blk.18.attn_output.weight | Block 18 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  169 | blk.18.attn_q.weight      | Block 18 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  170 | blk.18.attn_v.weight      | Block 18 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  171 | blk.18.ffn_down.weight    | Block 18 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  172 | blk.18.ffn_gate.weight    | Block 18 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  173 | blk.18.ffn_norm.weight    | Block 18 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  174 | blk.18.ffn_up.weight      | Block 18 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.18: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  175 | blk.19.attn_k.weight      | Block 19 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  176 | blk.19.attn_norm.weight   | Block 19 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  177 | blk.19.attn_output.weight | Block 19 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  178 | blk.19.attn_q.weight      | Block 19 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  179 | blk.19.attn_v.weight      | Block 19 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  180 | blk.19.ffn_down.weight    | Block 19 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  181 | blk.19.ffn_gate.weight    | Block 19 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  182 | blk.19.ffn_norm.weight    | Block 19 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  183 | blk.19.ffn_up.weight      | Block 19 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.19: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  184 | blk.20.attn_k.weight      | Block 20 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  185 | blk.20.attn_norm.weight   | Block 20 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  186 | blk.20.attn_output.weight | Block 20 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  187 | blk.20.attn_q.weight      | Block 20 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  188 | blk.20.attn_v.weight      | Block 20 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  189 | blk.20.ffn_down.weight    | Block 20 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  190 | blk.20.ffn_gate.weight    | Block 20 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  191 | blk.20.ffn_norm.weight    | Block 20 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  192 | blk.20.ffn_up.weight      | Block 20 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.20: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  193 | blk.21.attn_k.weight      | Block 21 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  194 | blk.21.attn_norm.weight   | Block 21 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  195 | blk.21.attn_output.weight | Block 21 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  196 | blk.21.attn_q.weight      | Block 21 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  197 | blk.21.attn_v.weight      | Block 21 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  198 | blk.21.ffn_down.weight    | Block 21 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  199 | blk.21.ffn_gate.weight    | Block 21 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  200 | blk.21.ffn_norm.weight    | Block 21 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  201 | blk.21.ffn_up.weight      | Block 21 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.21: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  202 | blk.22.attn_k.weight      | Block 22 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  203 | blk.22.attn_norm.weight   | Block 22 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  204 | blk.22.attn_output.weight | Block 22 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  205 | blk.22.attn_q.weight      | Block 22 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  206 | blk.22.attn_v.weight      | Block 22 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  207 | blk.22.ffn_down.weight    | Block 22 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  208 | blk.22.ffn_gate.weight    | Block 22 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  209 | blk.22.ffn_norm.weight    | Block 22 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  210 | blk.22.ffn_up.weight      | Block 22 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.22: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  211 | blk.23.attn_k.weight      | Block 23 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  212 | blk.23.attn_norm.weight   | Block 23 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  213 | blk.23.attn_output.weight | Block 23 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  214 | blk.23.attn_q.weight      | Block 23 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  215 | blk.23.attn_v.weight      | Block 23 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  216 | blk.23.ffn_down.weight    | Block 23 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  217 | blk.23.ffn_gate.weight    | Block 23 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  218 | blk.23.ffn_norm.weight    | Block 23 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  219 | blk.23.ffn_up.weight      | Block 23 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.23: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  220 | blk.24.attn_k.weight      | Block 24 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  221 | blk.24.attn_norm.weight   | Block 24 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  222 | blk.24.attn_output.weight | Block 24 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  223 | blk.24.attn_q.weight      | Block 24 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  224 | blk.24.attn_v.weight      | Block 24 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  225 | blk.24.ffn_down.weight    | Block 24 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  226 | blk.24.ffn_gate.weight    | Block 24 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  227 | blk.24.ffn_norm.weight    | Block 24 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  228 | blk.24.ffn_up.weight      | Block 24 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.24: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  229 | blk.25.attn_k.weight      | Block 25 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  230 | blk.25.attn_norm.weight   | Block 25 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  231 | blk.25.attn_output.weight | Block 25 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  232 | blk.25.attn_q.weight      | Block 25 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  233 | blk.25.attn_v.weight      | Block 25 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  234 | blk.25.ffn_down.weight    | Block 25 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  235 | blk.25.ffn_gate.weight    | Block 25 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  236 | blk.25.ffn_norm.weight    | Block 25 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  237 | blk.25.ffn_up.weight      | Block 25 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.25: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  238 | blk.26.attn_k.weight      | Block 26 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  239 | blk.26.attn_norm.weight   | Block 26 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  240 | blk.26.attn_output.weight | Block 26 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  241 | blk.26.attn_q.weight      | Block 26 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  242 | blk.26.attn_v.weight      | Block 26 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  243 | blk.26.ffn_down.weight    | Block 26 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  244 | blk.26.ffn_gate.weight    | Block 26 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  245 | blk.26.ffn_norm.weight    | Block 26 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  246 | blk.26.ffn_up.weight      | Block 26 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.26: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  247 | blk.27.attn_k.weight      | Block 27 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  248 | blk.27.attn_norm.weight   | Block 27 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  249 | blk.27.attn_output.weight | Block 27 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  250 | blk.27.attn_q.weight      | Block 27 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  251 | blk.27.attn_v.weight      | Block 27 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  252 | blk.27.ffn_down.weight    | Block 27 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  253 | blk.27.ffn_gate.weight    | Block 27 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  254 | blk.27.ffn_norm.weight    | Block 27 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  255 | blk.27.ffn_up.weight      | Block 27 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.27: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  256 | blk.28.attn_k.weight      | Block 28 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  257 | blk.28.attn_norm.weight   | Block 28 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  258 | blk.28.attn_output.weight | Block 28 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  259 | blk.28.attn_q.weight      | Block 28 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  260 | blk.28.attn_v.weight      | Block 28 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  261 | blk.28.ffn_down.weight    | Block 28 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  262 | blk.28.ffn_gate.weight    | Block 28 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  263 | blk.28.ffn_norm.weight    | Block 28 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  264 | blk.28.ffn_up.weight      | Block 28 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.28: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  265 | blk.29.attn_k.weight      | Block 29 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  266 | blk.29.attn_norm.weight   | Block 29 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  267 | blk.29.attn_output.weight | Block 29 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  268 | blk.29.attn_q.weight      | Block 29 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  269 | blk.29.attn_v.weight      | Block 29 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  270 | blk.29.ffn_down.weight    | Block 29 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  271 | blk.29.ffn_gate.weight    | Block 29 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  272 | blk.29.ffn_norm.weight    | Block 29 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  273 | blk.29.ffn_up.weight      | Block 29 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.29: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  274 | blk.30.attn_k.weight      | Block 30 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  275 | blk.30.attn_norm.weight   | Block 30 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  276 | blk.30.attn_output.weight | Block 30 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  277 | blk.30.attn_q.weight      | Block 30 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  278 | blk.30.attn_v.weight      | Block 30 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  279 | blk.30.ffn_down.weight    | Block 30 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  280 | blk.30.ffn_gate.weight    | Block 30 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  281 | blk.30.ffn_norm.weight    | Block 30 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  282 | blk.30.ffn_up.weight      | Block 30 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.30: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  283 | blk.31.attn_k.weight      | Block 31 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q5_K |
+|  284 | blk.31.attn_norm.weight   | Block 31 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  285 | blk.31.attn_output.weight | Block 31 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  286 | blk.31.attn_q.weight      | Block 31 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q5_K |
+|  287 | blk.31.attn_v.weight      | Block 31 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  288 | blk.31.ffn_down.weight    | Block 31 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  289 | blk.31.ffn_gate.weight    | Block 31 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  290 | blk.31.ffn_norm.weight    | Block 31 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  291 | blk.31.ffn_up.weight      | Block 31 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.31: (~218M) 218112000
+- Percentage of total elements: 2.72%

scores/Llama-Guard-3-8B-Q8_0.md ADDED Viewed

	@@ -0,0 +1,978 @@

+# Llama-Guard-3-8B-Q8_0.gguf - GGUF Internal File Dump
+- Endian: LITTLE endian
+## Key Value Metadata Store
+There are 39 key-value pairs in this file
+| POS | TYPE     |  Count | Key                                    | Value                                                               |
+|----:|:---------|-------:|:---------------------------------------|:--------------------------------------------------------------------|
+|   1 | UINT32   |      1 | GGUF.version                           | 3                                                                   |
+|   2 | UINT64   |      1 | GGUF.tensor_count                      | 292                                                                 |
+|   3 | UINT64   |      1 | GGUF.kv_count                          | 36                                                                  |
+|   4 | STRING   |      1 | general.architecture                   | `llama`                                                             |
+|   5 | STRING   |      1 | general.type                           | `model`                                                             |
+|   6 | STRING   |      1 | general.name                           | `Llama Guard 3 8B`                                                  |
+|   7 | STRING   |      1 | general.basename                       | `Llama-Guard-3`                                                     |
+|   8 | STRING   |      1 | general.size_label                     | `8B`                                                                |
+|   9 | STRING   |      1 | general.license                        | `llama3.1`                                                          |
+|  10 | UINT32   |      1 | general.base_model.count               | 1                                                                   |
+|  11 | STRING   |      1 | general.base_model.0.name              | `Meta Llama 3.1 8B`                                                 |
+|  12 | STRING   |      1 | general.base_model.0.organization      | `Meta Llama`                                                        |
+|  13 | STRING   |      1 | general.base_model.0.repo_url          | `https://huggingface.co/meta-llama/Meta-Llama-3.1-8B`               |
+|  14 | [STRING] |      6 | general.tags                           | [ `facebook`, `meta`, `pytorch`, `llama`, `llama-3`, ... ]          |
+|  15 | [STRING] |      1 | general.languages                      | [ `en` ]                                                            |
+|  16 | UINT32   |      1 | llama.block_count                      | 32                                                                  |
+|  17 | UINT32   |      1 | llama.context_length                   | 131072                                                              |
+|  18 | UINT32   |      1 | llama.embedding_length                 | 4096                                                                |
+|  19 | UINT32   |      1 | llama.feed_forward_length              | 14336                                                               |
+|  20 | UINT32   |      1 | llama.attention.head_count             | 32                                                                  |
+|  21 | UINT32   |      1 | llama.attention.head_count_kv          | 8                                                                   |
+|  22 | FLOAT32  |      1 | llama.rope.freq_base                   | 500000.0                                                            |
+|  23 | FLOAT32  |      1 | llama.attention.layer_norm_rms_epsilon | 1e-05                                                               |
+|  24 | UINT32   |      1 | llama.vocab_size                       | 128256                                                              |
+|  25 | UINT32   |      1 | llama.rope.dimension_count             | 128                                                                 |
+|  26 | STRING   |      1 | tokenizer.ggml.model                   | `gpt2`                                                              |
+|  27 | STRING   |      1 | tokenizer.ggml.pre                     | `smaug-bpe`                                                         |
+|  28 | [STRING] | 128256 | tokenizer.ggml.tokens                  | [ `!`, `"`, `#`, `$`, `%`, ... ]                                    |
+|  29 | [INT32]  | 128256 | tokenizer.ggml.token_type              | [ 1, 1, 1, 1, 1, 1, 1, ... ]                                        |
+|  30 | [STRING] | 280147 | tokenizer.ggml.merges                  | [ `Ġ Ġ`, `Ġ ĠĠĠ`, `ĠĠ ĠĠ`, `ĠĠĠ Ġ`, `i n`, ... ]                    |
+|  31 | UINT32   |      1 | tokenizer.ggml.bos_token_id            | 128000                                                              |
+|  32 | UINT32   |      1 | tokenizer.ggml.eos_token_id            | 128009                                                              |
+|  33 | STRING   |      1 | tokenizer.chat_template                | `{% if messages|length % 2 == 0`...`assistant<|end_header_id|>" }}` |
+|  34 | UINT32   |      1 | general.quantization_version           | 2                                                                   |
+|  35 | UINT32   |      1 | general.file_type                      | 7                                                                   |
+|  36 | STRING   |      1 | quantize.imatrix.file                  | `./imatrix/imatrix-Llama-Guard-3-8B-small.dat`                      |
+|  37 | STRING   |      1 | quantize.imatrix.dataset               | `../../datasets/imatrix/calibration_eur_small.txt`                  |
+|  38 | INT32    |      1 | quantize.imatrix.entries_count         | 224                                                                 |
+|  39 | INT32    |      1 | quantize.imatrix.chunks_count          | 962                                                                 |
+## Tensors Overview ~8B Elements
+Total number of elements in all tensors: 8030261312 Elements
+- [Llama-Guard-3-8B-Q8\_0.gguf - GGUF Internal File Dump](#llama-guard-3-8b-q8_0gguf---gguf-internal-file-dump)
+  - [Key Value Metadata Store](#key-value-metadata-store)
+  - [Tensors Overview ~8B Elements](#tensors-overview-8b-elements)
+    - [Tensor Data Offset](#tensor-data-offset)
+    - [Base Tensor Group : ~1B Elements](#base-tensor-group--1b-elements)
+    - [Block 0 Tensor Group : ~218M Elements](#block-0-tensor-group--218m-elements)
+    - [Block 1 Tensor Group : ~218M Elements](#block-1-tensor-group--218m-elements)
+    - [Block 2 Tensor Group : ~218M Elements](#block-2-tensor-group--218m-elements)
+    - [Block 3 Tensor Group : ~218M Elements](#block-3-tensor-group--218m-elements)
+    - [Block 4 Tensor Group : ~218M Elements](#block-4-tensor-group--218m-elements)
+    - [Block 5 Tensor Group : ~218M Elements](#block-5-tensor-group--218m-elements)
+    - [Block 6 Tensor Group : ~218M Elements](#block-6-tensor-group--218m-elements)
+    - [Block 7 Tensor Group : ~218M Elements](#block-7-tensor-group--218m-elements)
+    - [Block 8 Tensor Group : ~218M Elements](#block-8-tensor-group--218m-elements)
+    - [Block 9 Tensor Group : ~218M Elements](#block-9-tensor-group--218m-elements)
+    - [Block 10 Tensor Group : ~218M Elements](#block-10-tensor-group--218m-elements)
+    - [Block 11 Tensor Group : ~218M Elements](#block-11-tensor-group--218m-elements)
+    - [Block 12 Tensor Group : ~218M Elements](#block-12-tensor-group--218m-elements)
+    - [Block 13 Tensor Group : ~218M Elements](#block-13-tensor-group--218m-elements)
+    - [Block 14 Tensor Group : ~218M Elements](#block-14-tensor-group--218m-elements)
+    - [Block 15 Tensor Group : ~218M Elements](#block-15-tensor-group--218m-elements)
+    - [Block 16 Tensor Group : ~218M Elements](#block-16-tensor-group--218m-elements)
+    - [Block 17 Tensor Group : ~218M Elements](#block-17-tensor-group--218m-elements)
+    - [Block 18 Tensor Group : ~218M Elements](#block-18-tensor-group--218m-elements)
+    - [Block 19 Tensor Group : ~218M Elements](#block-19-tensor-group--218m-elements)
+    - [Block 20 Tensor Group : ~218M Elements](#block-20-tensor-group--218m-elements)
+    - [Block 21 Tensor Group : ~218M Elements](#block-21-tensor-group--218m-elements)
+    - [Block 22 Tensor Group : ~218M Elements](#block-22-tensor-group--218m-elements)
+    - [Block 23 Tensor Group : ~218M Elements](#block-23-tensor-group--218m-elements)
+    - [Block 24 Tensor Group : ~218M Elements](#block-24-tensor-group--218m-elements)
+    - [Block 25 Tensor Group : ~218M Elements](#block-25-tensor-group--218m-elements)
+    - [Block 26 Tensor Group : ~218M Elements](#block-26-tensor-group--218m-elements)
+    - [Block 27 Tensor Group : ~218M Elements](#block-27-tensor-group--218m-elements)
+    - [Block 28 Tensor Group : ~218M Elements](#block-28-tensor-group--218m-elements)
+    - [Block 29 Tensor Group : ~218M Elements](#block-29-tensor-group--218m-elements)
+    - [Block 30 Tensor Group : ~218M Elements](#block-30-tensor-group--218m-elements)
+    - [Block 31 Tensor Group : ~218M Elements](#block-31-tensor-group--218m-elements)
+### Tensor Data Offset
+This table contains the offset and data segment relative to start of file
+| T_ID | Tensor Layer Name         |  Data Offset (B) |    Data Size (B) |
+|-----:|:--------------------------|-----------------:|-----------------:|
+|    0 | output.weight             |         0x779880 |       0x21450000 |
+|    1 | output_norm.weight        |       0x21bc9880 |           0x4000 |
+|    2 | rope_freqs.weight         |       0x21bcd880 |            0x100 |
+|    3 | token_embd.weight         |       0x21bcd980 |        0xd746000 |
+|    4 | blk.0.attn_k.weight       |       0x2f313980 |         0x348000 |
+|    5 | blk.0.attn_norm.weight    |       0x2f65b980 |           0x4000 |
+|    6 | blk.0.attn_output.weight  |       0x2f65f980 |        0x1100000 |
+|    7 | blk.0.attn_q.weight       |       0x3075f980 |         0xd20000 |
+|    8 | blk.0.attn_v.weight       |       0x3147f980 |         0x440000 |
+|    9 | blk.0.ffn_down.weight     |       0x318bf980 |        0x3b80000 |
+|   10 | blk.0.ffn_gate.weight     |       0x3543f980 |        0x2df0000 |
+|   11 | blk.0.ffn_norm.weight     |       0x3822f980 |           0x4000 |
+|   12 | blk.0.ffn_up.weight       |       0x38233980 |        0x2df0000 |
+|   13 | blk.1.attn_k.weight       |       0x3b023980 |         0x348000 |
+|   14 | blk.1.attn_norm.weight    |       0x3b36b980 |           0x4000 |
+|   15 | blk.1.attn_output.weight  |       0x3b36f980 |        0x1100000 |
+|   16 | blk.1.attn_q.weight       |       0x3c46f980 |         0xd20000 |
+|   17 | blk.1.attn_v.weight       |       0x3d18f980 |         0x440000 |
+|   18 | blk.1.ffn_down.weight     |       0x3d5cf980 |        0x3b80000 |
+|   19 | blk.1.ffn_gate.weight     |       0x4114f980 |        0x2df0000 |
+|   20 | blk.1.ffn_norm.weight     |       0x43f3f980 |           0x4000 |
+|   21 | blk.1.ffn_up.weight       |       0x43f43980 |        0x2df0000 |
+|   22 | blk.2.attn_k.weight       |       0x46d33980 |         0x348000 |
+|   23 | blk.2.attn_norm.weight    |       0x4707b980 |           0x4000 |
+|   24 | blk.2.attn_output.weight  |       0x4707f980 |        0x1100000 |
+|   25 | blk.2.attn_q.weight       |       0x4817f980 |         0xd20000 |
+|   26 | blk.2.attn_v.weight       |       0x48e9f980 |         0x440000 |
+|   27 | blk.2.ffn_down.weight     |       0x492df980 |        0x3b80000 |
+|   28 | blk.2.ffn_gate.weight     |       0x4ce5f980 |        0x2df0000 |
+|   29 | blk.2.ffn_norm.weight     |       0x4fc4f980 |           0x4000 |
+|   30 | blk.2.ffn_up.weight       |       0x4fc53980 |        0x2df0000 |
+|   31 | blk.3.attn_k.weight       |       0x52a43980 |         0x348000 |
+|   32 | blk.3.attn_norm.weight    |       0x52d8b980 |           0x4000 |
+|   33 | blk.3.attn_output.weight  |       0x52d8f980 |        0x1100000 |
+|   34 | blk.3.attn_q.weight       |       0x53e8f980 |         0xd20000 |
+|   35 | blk.3.attn_v.weight       |       0x54baf980 |         0x440000 |
+|   36 | blk.3.ffn_down.weight     |       0x54fef980 |        0x3b80000 |
+|   37 | blk.3.ffn_gate.weight     |       0x58b6f980 |        0x2df0000 |
+|   38 | blk.3.ffn_norm.weight     |       0x5b95f980 |           0x4000 |
+|   39 | blk.3.ffn_up.weight       |       0x5b963980 |        0x2df0000 |
+|   40 | blk.4.attn_k.weight       |       0x5e753980 |         0x348000 |
+|   41 | blk.4.attn_norm.weight    |       0x5ea9b980 |           0x4000 |
+|   42 | blk.4.attn_output.weight  |       0x5ea9f980 |        0x1100000 |
+|   43 | blk.4.attn_q.weight       |       0x5fb9f980 |         0xd20000 |
+|   44 | blk.4.attn_v.weight       |       0x608bf980 |         0x440000 |
+|   45 | blk.4.ffn_down.weight     |       0x60cff980 |        0x3b80000 |
+|   46 | blk.4.ffn_gate.weight     |       0x6487f980 |        0x2df0000 |
+|   47 | blk.4.ffn_norm.weight     |       0x6766f980 |           0x4000 |
+|   48 | blk.4.ffn_up.weight       |       0x67673980 |        0x2df0000 |
+|   49 | blk.5.attn_k.weight       |       0x6a463980 |         0x348000 |
+|   50 | blk.5.attn_norm.weight    |       0x6a7ab980 |           0x4000 |
+|   51 | blk.5.attn_output.weight  |       0x6a7af980 |        0x1100000 |
+|   52 | blk.5.attn_q.weight       |       0x6b8af980 |         0xd20000 |
+|   53 | blk.5.attn_v.weight       |       0x6c5cf980 |         0x440000 |
+|   54 | blk.5.ffn_down.weight     |       0x6ca0f980 |        0x3b80000 |
+|   55 | blk.5.ffn_gate.weight     |       0x7058f980 |        0x2df0000 |
+|   56 | blk.5.ffn_norm.weight     |       0x7337f980 |           0x4000 |
+|   57 | blk.5.ffn_up.weight       |       0x73383980 |        0x2df0000 |
+|   58 | blk.6.attn_k.weight       |       0x76173980 |         0x348000 |
+|   59 | blk.6.attn_norm.weight    |       0x764bb980 |           0x4000 |
+|   60 | blk.6.attn_output.weight  |       0x764bf980 |        0x1100000 |
+|   61 | blk.6.attn_q.weight       |       0x775bf980 |         0xd20000 |
+|   62 | blk.6.attn_v.weight       |       0x782df980 |         0x440000 |
+|   63 | blk.6.ffn_down.weight     |       0x7871f980 |        0x3b80000 |
+|   64 | blk.6.ffn_gate.weight     |       0x7c29f980 |        0x2df0000 |
+|   65 | blk.6.ffn_norm.weight     |       0x7f08f980 |           0x4000 |
+|   66 | blk.6.ffn_up.weight       |       0x7f093980 |        0x2df0000 |
+|   67 | blk.7.attn_k.weight       |       0x81e83980 |         0x348000 |
+|   68 | blk.7.attn_norm.weight    |       0x821cb980 |           0x4000 |
+|   69 | blk.7.attn_output.weight  |       0x821cf980 |        0x1100000 |
+|   70 | blk.7.attn_q.weight       |       0x832cf980 |         0xd20000 |
+|   71 | blk.7.attn_v.weight       |       0x83fef980 |         0x440000 |
+|   72 | blk.7.ffn_down.weight     |       0x8442f980 |        0x3b80000 |
+|   73 | blk.7.ffn_gate.weight     |       0x87faf980 |        0x2df0000 |
+|   74 | blk.7.ffn_norm.weight     |       0x8ad9f980 |           0x4000 |
+|   75 | blk.7.ffn_up.weight       |       0x8ada3980 |        0x2df0000 |
+|   76 | blk.8.attn_k.weight       |       0x8db93980 |         0x348000 |
+|   77 | blk.8.attn_norm.weight    |       0x8dedb980 |           0x4000 |
+|   78 | blk.8.attn_output.weight  |       0x8dedf980 |        0x1100000 |
+|   79 | blk.8.attn_q.weight       |       0x8efdf980 |         0xd20000 |
+|   80 | blk.8.attn_v.weight       |       0x8fcff980 |         0x440000 |
+|   81 | blk.8.ffn_down.weight     |       0x9013f980 |        0x3b80000 |
+|   82 | blk.8.ffn_gate.weight     |       0x93cbf980 |        0x2df0000 |
+|   83 | blk.8.ffn_norm.weight     |       0x96aaf980 |           0x4000 |
+|   84 | blk.8.ffn_up.weight       |       0x96ab3980 |        0x2df0000 |
+|   85 | blk.9.attn_k.weight       |       0x998a3980 |         0x348000 |
+|   86 | blk.9.attn_norm.weight    |       0x99beb980 |           0x4000 |
+|   87 | blk.9.attn_output.weight  |       0x99bef980 |        0x1100000 |
+|   88 | blk.9.attn_q.weight       |       0x9acef980 |         0xd20000 |
+|   89 | blk.9.attn_v.weight       |       0x9ba0f980 |         0x440000 |
+|   90 | blk.9.ffn_down.weight     |       0x9be4f980 |        0x3b80000 |
+|   91 | blk.9.ffn_gate.weight     |       0x9f9cf980 |        0x2df0000 |
+|   92 | blk.9.ffn_norm.weight     |       0xa27bf980 |           0x4000 |
+|   93 | blk.9.ffn_up.weight       |       0xa27c3980 |        0x2df0000 |
+|   94 | blk.10.attn_k.weight      |       0xa55b3980 |         0x348000 |
+|   95 | blk.10.attn_norm.weight   |       0xa58fb980 |           0x4000 |
+|   96 | blk.10.attn_output.weight |       0xa58ff980 |        0x1100000 |
+|   97 | blk.10.attn_q.weight      |       0xa69ff980 |         0xd20000 |
+|   98 | blk.10.attn_v.weight      |       0xa771f980 |         0x440000 |
+|   99 | blk.10.ffn_down.weight    |       0xa7b5f980 |        0x3b80000 |
+|  100 | blk.10.ffn_gate.weight    |       0xab6df980 |        0x2df0000 |
+|  101 | blk.10.ffn_norm.weight    |       0xae4cf980 |           0x4000 |
+|  102 | blk.10.ffn_up.weight      |       0xae4d3980 |        0x2df0000 |
+|  103 | blk.11.attn_k.weight      |       0xb12c3980 |         0x348000 |
+|  104 | blk.11.attn_norm.weight   |       0xb160b980 |           0x4000 |
+|  105 | blk.11.attn_output.weight |       0xb160f980 |        0x1100000 |
+|  106 | blk.11.attn_q.weight      |       0xb270f980 |         0xd20000 |
+|  107 | blk.11.attn_v.weight      |       0xb342f980 |         0x440000 |
+|  108 | blk.11.ffn_down.weight    |       0xb386f980 |        0x3b80000 |
+|  109 | blk.11.ffn_gate.weight    |       0xb73ef980 |        0x2df0000 |
+|  110 | blk.11.ffn_norm.weight    |       0xba1df980 |           0x4000 |
+|  111 | blk.11.ffn_up.weight      |       0xba1e3980 |        0x2df0000 |
+|  112 | blk.12.attn_k.weight      |       0xbcfd3980 |         0x348000 |
+|  113 | blk.12.attn_norm.weight   |       0xbd31b980 |           0x4000 |
+|  114 | blk.12.attn_output.weight |       0xbd31f980 |        0x1100000 |
+|  115 | blk.12.attn_q.weight      |       0xbe41f980 |         0xd20000 |
+|  116 | blk.12.attn_v.weight      |       0xbf13f980 |         0x440000 |
+|  117 | blk.12.ffn_down.weight    |       0xbf57f980 |        0x3b80000 |
+|  118 | blk.12.ffn_gate.weight    |       0xc30ff980 |        0x2df0000 |
+|  119 | blk.12.ffn_norm.weight    |       0xc5eef980 |           0x4000 |
+|  120 | blk.12.ffn_up.weight      |       0xc5ef3980 |        0x2df0000 |
+|  121 | blk.13.attn_k.weight      |       0xc8ce3980 |         0x440000 |
+|  122 | blk.13.attn_norm.weight   |       0xc9123980 |           0x4000 |
+|  123 | blk.13.attn_output.weight |       0xc9127980 |        0x1100000 |
+|  124 | blk.13.attn_q.weight      |       0xca227980 |        0x1100000 |
+|  125 | blk.13.attn_v.weight      |       0xcb327980 |         0x800000 |
+|  126 | blk.13.ffn_down.weight    |       0xcbb27980 |        0x3b80000 |
+|  127 | blk.13.ffn_gate.weight    |       0xcf6a7980 |        0x2df0000 |
+|  128 | blk.13.ffn_norm.weight    |       0xd2497980 |           0x4000 |
+|  129 | blk.13.ffn_up.weight      |       0xd249b980 |        0x2df0000 |
+|  130 | blk.14.attn_k.weight      |       0xd528b980 |         0x440000 |
+|  131 | blk.14.attn_norm.weight   |       0xd56cb980 |           0x4000 |
+|  132 | blk.14.attn_output.weight |       0xd56cf980 |        0x1100000 |
+|  133 | blk.14.attn_q.weight      |       0xd67cf980 |        0x1100000 |
+|  134 | blk.14.attn_v.weight      |       0xd78cf980 |         0x800000 |
+|  135 | blk.14.ffn_down.weight    |       0xd80cf980 |        0x3b80000 |
+|  136 | blk.14.ffn_gate.weight    |       0xdbc4f980 |        0x2df0000 |
+|  137 | blk.14.ffn_norm.weight    |       0xdea3f980 |           0x4000 |
+|  138 | blk.14.ffn_up.weight      |       0xdea43980 |        0x2df0000 |
+|  139 | blk.15.attn_k.weight      |       0xe1833980 |         0x348000 |
+|  140 | blk.15.attn_norm.weight   |       0xe1b7b980 |           0x4000 |
+|  141 | blk.15.attn_output.weight |       0xe1b7f980 |        0x1100000 |
+|  142 | blk.15.attn_q.weight      |       0xe2c7f980 |         0xd20000 |
+|  143 | blk.15.attn_v.weight      |       0xe399f980 |         0x440000 |
+|  144 | blk.15.ffn_down.weight    |       0xe3ddf980 |        0x3b80000 |
+|  145 | blk.15.ffn_gate.weight    |       0xe795f980 |        0x2df0000 |
+|  146 | blk.15.ffn_norm.weight    |       0xea74f980 |           0x4000 |
+|  147 | blk.15.ffn_up.weight      |       0xea753980 |        0x2df0000 |
+|  148 | blk.16.attn_k.weight      |       0xed543980 |         0x440000 |
+|  149 | blk.16.attn_norm.weight   |       0xed983980 |           0x4000 |
+|  150 | blk.16.attn_output.weight |       0xed987980 |        0x1100000 |
+|  151 | blk.16.attn_q.weight      |       0xeea87980 |        0x1100000 |
+|  152 | blk.16.attn_v.weight      |       0xefb87980 |         0x800000 |
+|  153 | blk.16.ffn_down.weight    |       0xf0387980 |        0x3b80000 |
+|  154 | blk.16.ffn_gate.weight    |       0xf3f07980 |        0x3b80000 |
+|  155 | blk.16.ffn_norm.weight    |       0xf7a87980 |           0x4000 |
+|  156 | blk.16.ffn_up.weight      |       0xf7a8b980 |        0x3b80000 |
+|  157 | blk.17.attn_k.weight      |       0xfb60b980 |         0x348000 |
+|  158 | blk.17.attn_norm.weight   |       0xfb953980 |           0x4000 |
+|  159 | blk.17.attn_output.weight |       0xfb957980 |        0x1100000 |
+|  160 | blk.17.attn_q.weight      |       0xfca57980 |         0xd20000 |
+|  161 | blk.17.attn_v.weight      |       0xfd777980 |         0x440000 |
+|  162 | blk.17.ffn_down.weight    |       0xfdbb7980 |        0x3b80000 |
+|  163 | blk.17.ffn_gate.weight    |      0x101737980 |        0x3b80000 |
+|  164 | blk.17.ffn_norm.weight    |      0x1052b7980 |           0x4000 |
+|  165 | blk.17.ffn_up.weight      |      0x1052bb980 |        0x3b80000 |
+|  166 | blk.18.attn_k.weight      |      0x108e3b980 |         0x440000 |
+|  167 | blk.18.attn_norm.weight   |      0x10927b980 |           0x4000 |
+|  168 | blk.18.attn_output.weight |      0x10927f980 |        0x1100000 |
+|  169 | blk.18.attn_q.weight      |      0x10a37f980 |        0x1100000 |
+|  170 | blk.18.attn_v.weight      |      0x10b47f980 |         0x800000 |
+|  171 | blk.18.ffn_down.weight    |      0x10bc7f980 |        0x3b80000 |
+|  172 | blk.18.ffn_gate.weight    |      0x10f7ff980 |        0x3b80000 |
+|  173 | blk.18.ffn_norm.weight    |      0x11337f980 |           0x4000 |
+|  174 | blk.18.ffn_up.weight      |      0x113383980 |        0x3b80000 |
+|  175 | blk.19.attn_k.weight      |      0x116f03980 |         0x440000 |
+|  176 | blk.19.attn_norm.weight   |      0x117343980 |           0x4000 |
+|  177 | blk.19.attn_output.weight |      0x117347980 |        0x1100000 |
+|  178 | blk.19.attn_q.weight      |      0x118447980 |        0x1100000 |
+|  179 | blk.19.attn_v.weight      |      0x119547980 |         0x800000 |
+|  180 | blk.19.ffn_down.weight    |      0x119d47980 |        0x3b80000 |
+|  181 | blk.19.ffn_gate.weight    |      0x11d8c7980 |        0x3b80000 |
+|  182 | blk.19.ffn_norm.weight    |      0x121447980 |           0x4000 |
+|  183 | blk.19.ffn_up.weight      |      0x12144b980 |        0x3b80000 |
+|  184 | blk.20.attn_k.weight      |      0x124fcb980 |         0x440000 |
+|  185 | blk.20.attn_norm.weight   |      0x12540b980 |           0x4000 |
+|  186 | blk.20.attn_output.weight |      0x12540f980 |        0x1100000 |
+|  187 | blk.20.attn_q.weight      |      0x12650f980 |        0x1100000 |
+|  188 | blk.20.attn_v.weight      |      0x12760f980 |         0x800000 |
+|  189 | blk.20.ffn_down.weight    |      0x127e0f980 |        0x3b80000 |
+|  190 | blk.20.ffn_gate.weight    |      0x12b98f980 |        0x3b80000 |
+|  191 | blk.20.ffn_norm.weight    |      0x12f50f980 |           0x4000 |
+|  192 | blk.20.ffn_up.weight      |      0x12f513980 |        0x3b80000 |
+|  193 | blk.21.attn_k.weight      |      0x133093980 |         0x440000 |
+|  194 | blk.21.attn_norm.weight   |      0x1334d3980 |           0x4000 |
+|  195 | blk.21.attn_output.weight |      0x1334d7980 |        0x1100000 |
+|  196 | blk.21.attn_q.weight      |      0x1345d7980 |        0x1100000 |
+|  197 | blk.21.attn_v.weight      |      0x1356d7980 |         0x800000 |
+|  198 | blk.21.ffn_down.weight    |      0x135ed7980 |        0x3b80000 |
+|  199 | blk.21.ffn_gate.weight    |      0x139a57980 |        0x3b80000 |
+|  200 | blk.21.ffn_norm.weight    |      0x13d5d7980 |           0x4000 |
+|  201 | blk.21.ffn_up.weight      |      0x13d5db980 |        0x3b80000 |
+|  202 | blk.22.attn_k.weight      |      0x14115b980 |         0x440000 |
+|  203 | blk.22.attn_norm.weight   |      0x14159b980 |           0x4000 |
+|  204 | blk.22.attn_output.weight |      0x14159f980 |        0x1100000 |
+|  205 | blk.22.attn_q.weight      |      0x14269f980 |        0x1100000 |
+|  206 | blk.22.attn_v.weight      |      0x14379f980 |         0x800000 |
+|  207 | blk.22.ffn_down.weight    |      0x143f9f980 |        0x3b80000 |
+|  208 | blk.22.ffn_gate.weight    |      0x147b1f980 |        0x3b80000 |
+|  209 | blk.22.ffn_norm.weight    |      0x14b69f980 |           0x4000 |
+|  210 | blk.22.ffn_up.weight      |      0x14b6a3980 |        0x3b80000 |
+|  211 | blk.23.attn_k.weight      |      0x14f223980 |         0x440000 |
+|  212 | blk.23.attn_norm.weight   |      0x14f663980 |           0x4000 |
+|  213 | blk.23.attn_output.weight |      0x14f667980 |        0x1100000 |
+|  214 | blk.23.attn_q.weight      |      0x150767980 |        0x1100000 |
+|  215 | blk.23.attn_v.weight      |      0x151867980 |         0x800000 |
+|  216 | blk.23.ffn_down.weight    |      0x152067980 |        0x3b80000 |
+|  217 | blk.23.ffn_gate.weight    |      0x155be7980 |        0x3b80000 |
+|  218 | blk.23.ffn_norm.weight    |      0x159767980 |           0x4000 |
+|  219 | blk.23.ffn_up.weight      |      0x15976b980 |        0x3b80000 |
+|  220 | blk.24.attn_k.weight      |      0x15d2eb980 |         0x440000 |
+|  221 | blk.24.attn_norm.weight   |      0x15d72b980 |           0x4000 |
+|  222 | blk.24.attn_output.weight |      0x15d72f980 |        0x1100000 |
+|  223 | blk.24.attn_q.weight      |      0x15e82f980 |        0x1100000 |
+|  224 | blk.24.attn_v.weight      |      0x15f92f980 |         0x800000 |
+|  225 | blk.24.ffn_down.weight    |      0x16012f980 |        0x3b80000 |
+|  226 | blk.24.ffn_gate.weight    |      0x163caf980 |        0x3b80000 |
+|  227 | blk.24.ffn_norm.weight    |      0x16782f980 |           0x4000 |
+|  228 | blk.24.ffn_up.weight      |      0x167833980 |        0x3b80000 |
+|  229 | blk.25.attn_k.weight      |      0x16b3b3980 |         0x440000 |
+|  230 | blk.25.attn_norm.weight   |      0x16b7f3980 |           0x4000 |
+|  231 | blk.25.attn_output.weight |      0x16b7f7980 |        0x1100000 |
+|  232 | blk.25.attn_q.weight      |      0x16c8f7980 |        0x1100000 |
+|  233 | blk.25.attn_v.weight      |      0x16d9f7980 |         0x800000 |
+|  234 | blk.25.ffn_down.weight    |      0x16e1f7980 |        0x3b80000 |
+|  235 | blk.25.ffn_gate.weight    |      0x171d77980 |        0x3b80000 |
+|  236 | blk.25.ffn_norm.weight    |      0x1758f7980 |           0x4000 |
+|  237 | blk.25.ffn_up.weight      |      0x1758fb980 |        0x3b80000 |
+|  238 | blk.26.attn_k.weight      |      0x17947b980 |         0x440000 |
+|  239 | blk.26.attn_norm.weight   |      0x1798bb980 |           0x4000 |
+|  240 | blk.26.attn_output.weight |      0x1798bf980 |        0x1100000 |
+|  241 | blk.26.attn_q.weight      |      0x17a9bf980 |        0x1100000 |
+|  242 | blk.26.attn_v.weight      |      0x17babf980 |         0x800000 |
+|  243 | blk.26.ffn_down.weight    |      0x17c2bf980 |        0x3b80000 |
+|  244 | blk.26.ffn_gate.weight    |      0x17fe3f980 |        0x3b80000 |
+|  245 | blk.26.ffn_norm.weight    |      0x1839bf980 |           0x4000 |
+|  246 | blk.26.ffn_up.weight      |      0x1839c3980 |        0x3b80000 |
+|  247 | blk.27.attn_k.weight      |      0x187543980 |         0x440000 |
+|  248 | blk.27.attn_norm.weight   |      0x187983980 |           0x4000 |
+|  249 | blk.27.attn_output.weight |      0x187987980 |        0x1100000 |
+|  250 | blk.27.attn_q.weight      |      0x188a87980 |        0x1100000 |
+|  251 | blk.27.attn_v.weight      |      0x189b87980 |         0x800000 |
+|  252 | blk.27.ffn_down.weight    |      0x18a387980 |        0x3b80000 |
+|  253 | blk.27.ffn_gate.weight    |      0x18df07980 |        0x3b80000 |
+|  254 | blk.27.ffn_norm.weight    |      0x191a87980 |           0x4000 |
+|  255 | blk.27.ffn_up.weight      |      0x191a8b980 |        0x3b80000 |
+|  256 | blk.28.attn_k.weight      |      0x19560b980 |         0x440000 |
+|  257 | blk.28.attn_norm.weight   |      0x195a4b980 |           0x4000 |
+|  258 | blk.28.attn_output.weight |      0x195a4f980 |        0x1100000 |
+|  259 | blk.28.attn_q.weight      |      0x196b4f980 |        0x1100000 |
+|  260 | blk.28.attn_v.weight      |      0x197c4f980 |         0x800000 |
+|  261 | blk.28.ffn_down.weight    |      0x19844f980 |        0x3b80000 |
+|  262 | blk.28.ffn_gate.weight    |      0x19bfcf980 |        0x3b80000 |
+|  263 | blk.28.ffn_norm.weight    |      0x19fb4f980 |           0x4000 |
+|  264 | blk.28.ffn_up.weight      |      0x19fb53980 |        0x3b80000 |
+|  265 | blk.29.attn_k.weight      |      0x1a36d3980 |         0x440000 |
+|  266 | blk.29.attn_norm.weight   |      0x1a3b13980 |           0x4000 |
+|  267 | blk.29.attn_output.weight |      0x1a3b17980 |        0x1100000 |
+|  268 | blk.29.attn_q.weight      |      0x1a4c17980 |        0x1100000 |
+|  269 | blk.29.attn_v.weight      |      0x1a5d17980 |         0x800000 |
+|  270 | blk.29.ffn_down.weight    |      0x1a6517980 |        0x3b80000 |
+|  271 | blk.29.ffn_gate.weight    |      0x1aa097980 |        0x3b80000 |
+|  272 | blk.29.ffn_norm.weight    |      0x1adc17980 |           0x4000 |
+|  273 | blk.29.ffn_up.weight      |      0x1adc1b980 |        0x3b80000 |
+|  274 | blk.30.attn_k.weight      |      0x1b179b980 |         0x440000 |
+|  275 | blk.30.attn_norm.weight   |      0x1b1bdb980 |           0x4000 |
+|  276 | blk.30.attn_output.weight |      0x1b1bdf980 |        0x1100000 |
+|  277 | blk.30.attn_q.weight      |      0x1b2cdf980 |        0x1100000 |
+|  278 | blk.30.attn_v.weight      |      0x1b3ddf980 |         0x800000 |
+|  279 | blk.30.ffn_down.weight    |      0x1b45df980 |        0x3b80000 |
+|  280 | blk.30.ffn_gate.weight    |      0x1b815f980 |        0x3b80000 |
+|  281 | blk.30.ffn_norm.weight    |      0x1bbcdf980 |           0x4000 |
+|  282 | blk.30.ffn_up.weight      |      0x1bbce3980 |        0x3b80000 |
+|  283 | blk.31.attn_k.weight      |      0x1bf863980 |         0x348000 |
+|  284 | blk.31.attn_norm.weight   |      0x1bfbab980 |           0x4000 |
+|  285 | blk.31.attn_output.weight |      0x1bfbaf980 |        0x1100000 |
+|  286 | blk.31.attn_q.weight      |      0x1c0caf980 |         0xd20000 |
+|  287 | blk.31.attn_v.weight      |      0x1c19cf980 |         0x440000 |
+|  288 | blk.31.ffn_down.weight    |      0x1c1e0f980 |        0x3b80000 |
+|  289 | blk.31.ffn_gate.weight    |      0x1c598f980 |        0x3b80000 |
+|  290 | blk.31.ffn_norm.weight    |      0x1c950f980 |           0x4000 |
+|  291 | blk.31.ffn_up.weight      |      0x1c9513980 |        0x3b80000 |
+### <a name="base">Base Tensor Group : ~1B Elements</a>
+| T_ID | Tensor Layer Name  | Human Friendly Tensor Layer Name | Elements          | Shape                 | Type |
+|-----:|:-------------------|:---------------------------------|:------------------|:----------------------|:-----|
+|    0 | output.weight      | Output (W)                       | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q8_0 |
+|    1 | output_norm.weight | Output Normalization (W)         | (  ~4K)      4096 | 4096 x      1 x 1 x 1 | F32  |
+|    2 | rope_freqs.weight  | Rope_Freqs (W)                   | (   64)        64 |   64 x      1 x 1 x 1 | F32  |
+|    3 | token_embd.weight  | Token Embedding (W)              | (~525M) 525336576 | 4096 x 128256 x 1 x 1 | Q3_K |
+- Total elements in base: ( ~1B) 1050677312
+- Percentage of total elements: 13.08%
+### <a name="blk_0">Block 0 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|    4 | blk.0.attn_k.weight      | Block 0 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|    5 | blk.0.attn_norm.weight   | Block 0 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|    6 | blk.0.attn_output.weight | Block 0 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|    7 | blk.0.attn_q.weight      | Block 0 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|    8 | blk.0.attn_v.weight      | Block 0 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|    9 | blk.0.ffn_down.weight    | Block 0 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   10 | blk.0.ffn_gate.weight    | Block 0 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|   11 | blk.0.ffn_norm.weight    | Block 0 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   12 | blk.0.ffn_up.weight      | Block 0 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.0: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_1">Block 1 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   13 | blk.1.attn_k.weight      | Block 1 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   14 | blk.1.attn_norm.weight   | Block 1 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   15 | blk.1.attn_output.weight | Block 1 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|   16 | blk.1.attn_q.weight      | Block 1 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   17 | blk.1.attn_v.weight      | Block 1 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|   18 | blk.1.ffn_down.weight    | Block 1 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   19 | blk.1.ffn_gate.weight    | Block 1 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|   20 | blk.1.ffn_norm.weight    | Block 1 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   21 | blk.1.ffn_up.weight      | Block 1 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.1: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_2">Block 2 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   22 | blk.2.attn_k.weight      | Block 2 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   23 | blk.2.attn_norm.weight   | Block 2 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   24 | blk.2.attn_output.weight | Block 2 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|   25 | blk.2.attn_q.weight      | Block 2 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   26 | blk.2.attn_v.weight      | Block 2 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|   27 | blk.2.ffn_down.weight    | Block 2 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   28 | blk.2.ffn_gate.weight    | Block 2 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|   29 | blk.2.ffn_norm.weight    | Block 2 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   30 | blk.2.ffn_up.weight      | Block 2 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.2: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_3">Block 3 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   31 | blk.3.attn_k.weight      | Block 3 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   32 | blk.3.attn_norm.weight   | Block 3 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   33 | blk.3.attn_output.weight | Block 3 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|   34 | blk.3.attn_q.weight      | Block 3 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   35 | blk.3.attn_v.weight      | Block 3 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|   36 | blk.3.ffn_down.weight    | Block 3 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   37 | blk.3.ffn_gate.weight    | Block 3 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|   38 | blk.3.ffn_norm.weight    | Block 3 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   39 | blk.3.ffn_up.weight      | Block 3 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.3: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_4">Block 4 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   40 | blk.4.attn_k.weight      | Block 4 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   41 | blk.4.attn_norm.weight   | Block 4 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   42 | blk.4.attn_output.weight | Block 4 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|   43 | blk.4.attn_q.weight      | Block 4 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   44 | blk.4.attn_v.weight      | Block 4 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|   45 | blk.4.ffn_down.weight    | Block 4 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   46 | blk.4.ffn_gate.weight    | Block 4 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|   47 | blk.4.ffn_norm.weight    | Block 4 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   48 | blk.4.ffn_up.weight      | Block 4 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.4: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_5">Block 5 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   49 | blk.5.attn_k.weight      | Block 5 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   50 | blk.5.attn_norm.weight   | Block 5 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   51 | blk.5.attn_output.weight | Block 5 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|   52 | blk.5.attn_q.weight      | Block 5 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   53 | blk.5.attn_v.weight      | Block 5 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|   54 | blk.5.ffn_down.weight    | Block 5 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   55 | blk.5.ffn_gate.weight    | Block 5 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|   56 | blk.5.ffn_norm.weight    | Block 5 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   57 | blk.5.ffn_up.weight      | Block 5 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.5: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_6">Block 6 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   58 | blk.6.attn_k.weight      | Block 6 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   59 | blk.6.attn_norm.weight   | Block 6 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   60 | blk.6.attn_output.weight | Block 6 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|   61 | blk.6.attn_q.weight      | Block 6 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   62 | blk.6.attn_v.weight      | Block 6 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|   63 | blk.6.ffn_down.weight    | Block 6 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   64 | blk.6.ffn_gate.weight    | Block 6 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|   65 | blk.6.ffn_norm.weight    | Block 6 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   66 | blk.6.ffn_up.weight      | Block 6 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.6: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_7">Block 7 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   67 | blk.7.attn_k.weight      | Block 7 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   68 | blk.7.attn_norm.weight   | Block 7 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   69 | blk.7.attn_output.weight | Block 7 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|   70 | blk.7.attn_q.weight      | Block 7 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   71 | blk.7.attn_v.weight      | Block 7 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|   72 | blk.7.ffn_down.weight    | Block 7 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   73 | blk.7.ffn_gate.weight    | Block 7 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|   74 | blk.7.ffn_norm.weight    | Block 7 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   75 | blk.7.ffn_up.weight      | Block 7 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.7: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_8">Block 8 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   76 | blk.8.attn_k.weight      | Block 8 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   77 | blk.8.attn_norm.weight   | Block 8 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   78 | blk.8.attn_output.weight | Block 8 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|   79 | blk.8.attn_q.weight      | Block 8 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   80 | blk.8.attn_v.weight      | Block 8 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|   81 | blk.8.ffn_down.weight    | Block 8 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   82 | blk.8.ffn_gate.weight    | Block 8 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|   83 | blk.8.ffn_norm.weight    | Block 8 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   84 | blk.8.ffn_up.weight      | Block 8 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.8: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_9">Block 9 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name        | Human Friendly Tensor Layer Name               | Elements        | Shape                 | Type |
+|-----:|:-------------------------|:-----------------------------------------------|:----------------|:----------------------|:-----|
+|   85 | blk.9.attn_k.weight      | Block 9 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   86 | blk.9.attn_norm.weight   | Block 9 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   87 | blk.9.attn_output.weight | Block 9 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|   88 | blk.9.attn_q.weight      | Block 9 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   89 | blk.9.attn_v.weight      | Block 9 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|   90 | blk.9.ffn_down.weight    | Block 9 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|   91 | blk.9.ffn_gate.weight    | Block 9 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|   92 | blk.9.ffn_norm.weight    | Block 9 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   93 | blk.9.ffn_up.weight      | Block 9 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.9: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_10">Block 10 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|   94 | blk.10.attn_k.weight      | Block 10 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|   95 | blk.10.attn_norm.weight   | Block 10 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|   96 | blk.10.attn_output.weight | Block 10 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|   97 | blk.10.attn_q.weight      | Block 10 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|   98 | blk.10.attn_v.weight      | Block 10 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|   99 | blk.10.ffn_down.weight    | Block 10 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  100 | blk.10.ffn_gate.weight    | Block 10 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  101 | blk.10.ffn_norm.weight    | Block 10 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  102 | blk.10.ffn_up.weight      | Block 10 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.10: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_11">Block 11 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  103 | blk.11.attn_k.weight      | Block 11 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  104 | blk.11.attn_norm.weight   | Block 11 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  105 | blk.11.attn_output.weight | Block 11 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  106 | blk.11.attn_q.weight      | Block 11 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  107 | blk.11.attn_v.weight      | Block 11 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  108 | blk.11.ffn_down.weight    | Block 11 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  109 | blk.11.ffn_gate.weight    | Block 11 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  110 | blk.11.ffn_norm.weight    | Block 11 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  111 | blk.11.ffn_up.weight      | Block 11 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.11: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_12">Block 12 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  112 | blk.12.attn_k.weight      | Block 12 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  113 | blk.12.attn_norm.weight   | Block 12 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  114 | blk.12.attn_output.weight | Block 12 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  115 | blk.12.attn_q.weight      | Block 12 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  116 | blk.12.attn_v.weight      | Block 12 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  117 | blk.12.ffn_down.weight    | Block 12 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  118 | blk.12.ffn_gate.weight    | Block 12 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  119 | blk.12.ffn_norm.weight    | Block 12 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  120 | blk.12.ffn_up.weight      | Block 12 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.12: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_13">Block 13 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  121 | blk.13.attn_k.weight      | Block 13 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  122 | blk.13.attn_norm.weight   | Block 13 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  123 | blk.13.attn_output.weight | Block 13 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  124 | blk.13.attn_q.weight      | Block 13 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  125 | blk.13.attn_v.weight      | Block 13 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  126 | blk.13.ffn_down.weight    | Block 13 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  127 | blk.13.ffn_gate.weight    | Block 13 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  128 | blk.13.ffn_norm.weight    | Block 13 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  129 | blk.13.ffn_up.weight      | Block 13 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.13: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_14">Block 14 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  130 | blk.14.attn_k.weight      | Block 14 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  131 | blk.14.attn_norm.weight   | Block 14 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  132 | blk.14.attn_output.weight | Block 14 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  133 | blk.14.attn_q.weight      | Block 14 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  134 | blk.14.attn_v.weight      | Block 14 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  135 | blk.14.ffn_down.weight    | Block 14 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  136 | blk.14.ffn_gate.weight    | Block 14 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  137 | blk.14.ffn_norm.weight    | Block 14 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  138 | blk.14.ffn_up.weight      | Block 14 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.14: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_15">Block 15 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  139 | blk.15.attn_k.weight      | Block 15 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  140 | blk.15.attn_norm.weight   | Block 15 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  141 | blk.15.attn_output.weight | Block 15 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  142 | blk.15.attn_q.weight      | Block 15 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  143 | blk.15.attn_v.weight      | Block 15 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  144 | blk.15.ffn_down.weight    | Block 15 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  145 | blk.15.ffn_gate.weight    | Block 15 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+|  146 | blk.15.ffn_norm.weight    | Block 15 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  147 | blk.15.ffn_up.weight      | Block 15 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q6_K |
+- Total elements in blk.15: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_16">Block 16 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  148 | blk.16.attn_k.weight      | Block 16 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  149 | blk.16.attn_norm.weight   | Block 16 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  150 | blk.16.attn_output.weight | Block 16 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  151 | blk.16.attn_q.weight      | Block 16 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  152 | blk.16.attn_v.weight      | Block 16 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  153 | blk.16.ffn_down.weight    | Block 16 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  154 | blk.16.ffn_gate.weight    | Block 16 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  155 | blk.16.ffn_norm.weight    | Block 16 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  156 | blk.16.ffn_up.weight      | Block 16 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.16: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_17">Block 17 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  157 | blk.17.attn_k.weight      | Block 17 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  158 | blk.17.attn_norm.weight   | Block 17 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  159 | blk.17.attn_output.weight | Block 17 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  160 | blk.17.attn_q.weight      | Block 17 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  161 | blk.17.attn_v.weight      | Block 17 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  162 | blk.17.ffn_down.weight    | Block 17 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  163 | blk.17.ffn_gate.weight    | Block 17 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  164 | blk.17.ffn_norm.weight    | Block 17 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  165 | blk.17.ffn_up.weight      | Block 17 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.17: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_18">Block 18 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  166 | blk.18.attn_k.weight      | Block 18 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  167 | blk.18.attn_norm.weight   | Block 18 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  168 | blk.18.attn_output.weight | Block 18 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  169 | blk.18.attn_q.weight      | Block 18 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  170 | blk.18.attn_v.weight      | Block 18 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  171 | blk.18.ffn_down.weight    | Block 18 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  172 | blk.18.ffn_gate.weight    | Block 18 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  173 | blk.18.ffn_norm.weight    | Block 18 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  174 | blk.18.ffn_up.weight      | Block 18 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.18: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_19">Block 19 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  175 | blk.19.attn_k.weight      | Block 19 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  176 | blk.19.attn_norm.weight   | Block 19 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  177 | blk.19.attn_output.weight | Block 19 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  178 | blk.19.attn_q.weight      | Block 19 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  179 | blk.19.attn_v.weight      | Block 19 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  180 | blk.19.ffn_down.weight    | Block 19 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  181 | blk.19.ffn_gate.weight    | Block 19 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  182 | blk.19.ffn_norm.weight    | Block 19 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  183 | blk.19.ffn_up.weight      | Block 19 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.19: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_20">Block 20 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  184 | blk.20.attn_k.weight      | Block 20 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  185 | blk.20.attn_norm.weight   | Block 20 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  186 | blk.20.attn_output.weight | Block 20 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  187 | blk.20.attn_q.weight      | Block 20 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  188 | blk.20.attn_v.weight      | Block 20 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  189 | blk.20.ffn_down.weight    | Block 20 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  190 | blk.20.ffn_gate.weight    | Block 20 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  191 | blk.20.ffn_norm.weight    | Block 20 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  192 | blk.20.ffn_up.weight      | Block 20 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.20: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_21">Block 21 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  193 | blk.21.attn_k.weight      | Block 21 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  194 | blk.21.attn_norm.weight   | Block 21 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  195 | blk.21.attn_output.weight | Block 21 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  196 | blk.21.attn_q.weight      | Block 21 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  197 | blk.21.attn_v.weight      | Block 21 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  198 | blk.21.ffn_down.weight    | Block 21 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  199 | blk.21.ffn_gate.weight    | Block 21 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  200 | blk.21.ffn_norm.weight    | Block 21 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  201 | blk.21.ffn_up.weight      | Block 21 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.21: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_22">Block 22 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  202 | blk.22.attn_k.weight      | Block 22 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  203 | blk.22.attn_norm.weight   | Block 22 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  204 | blk.22.attn_output.weight | Block 22 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  205 | blk.22.attn_q.weight      | Block 22 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  206 | blk.22.attn_v.weight      | Block 22 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  207 | blk.22.ffn_down.weight    | Block 22 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  208 | blk.22.ffn_gate.weight    | Block 22 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  209 | blk.22.ffn_norm.weight    | Block 22 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  210 | blk.22.ffn_up.weight      | Block 22 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.22: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_23">Block 23 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  211 | blk.23.attn_k.weight      | Block 23 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  212 | blk.23.attn_norm.weight   | Block 23 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  213 | blk.23.attn_output.weight | Block 23 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  214 | blk.23.attn_q.weight      | Block 23 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  215 | blk.23.attn_v.weight      | Block 23 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  216 | blk.23.ffn_down.weight    | Block 23 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  217 | blk.23.ffn_gate.weight    | Block 23 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  218 | blk.23.ffn_norm.weight    | Block 23 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  219 | blk.23.ffn_up.weight      | Block 23 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.23: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_24">Block 24 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  220 | blk.24.attn_k.weight      | Block 24 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  221 | blk.24.attn_norm.weight   | Block 24 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  222 | blk.24.attn_output.weight | Block 24 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  223 | blk.24.attn_q.weight      | Block 24 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  224 | blk.24.attn_v.weight      | Block 24 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  225 | blk.24.ffn_down.weight    | Block 24 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  226 | blk.24.ffn_gate.weight    | Block 24 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  227 | blk.24.ffn_norm.weight    | Block 24 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  228 | blk.24.ffn_up.weight      | Block 24 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.24: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_25">Block 25 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  229 | blk.25.attn_k.weight      | Block 25 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  230 | blk.25.attn_norm.weight   | Block 25 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  231 | blk.25.attn_output.weight | Block 25 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  232 | blk.25.attn_q.weight      | Block 25 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  233 | blk.25.attn_v.weight      | Block 25 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  234 | blk.25.ffn_down.weight    | Block 25 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  235 | blk.25.ffn_gate.weight    | Block 25 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  236 | blk.25.ffn_norm.weight    | Block 25 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  237 | blk.25.ffn_up.weight      | Block 25 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.25: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_26">Block 26 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  238 | blk.26.attn_k.weight      | Block 26 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  239 | blk.26.attn_norm.weight   | Block 26 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  240 | blk.26.attn_output.weight | Block 26 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  241 | blk.26.attn_q.weight      | Block 26 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  242 | blk.26.attn_v.weight      | Block 26 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  243 | blk.26.ffn_down.weight    | Block 26 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  244 | blk.26.ffn_gate.weight    | Block 26 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  245 | blk.26.ffn_norm.weight    | Block 26 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  246 | blk.26.ffn_up.weight      | Block 26 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.26: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_27">Block 27 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  247 | blk.27.attn_k.weight      | Block 27 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  248 | blk.27.attn_norm.weight   | Block 27 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  249 | blk.27.attn_output.weight | Block 27 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  250 | blk.27.attn_q.weight      | Block 27 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  251 | blk.27.attn_v.weight      | Block 27 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  252 | blk.27.ffn_down.weight    | Block 27 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  253 | blk.27.ffn_gate.weight    | Block 27 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  254 | blk.27.ffn_norm.weight    | Block 27 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  255 | blk.27.ffn_up.weight      | Block 27 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.27: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_28">Block 28 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  256 | blk.28.attn_k.weight      | Block 28 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  257 | blk.28.attn_norm.weight   | Block 28 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  258 | blk.28.attn_output.weight | Block 28 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  259 | blk.28.attn_q.weight      | Block 28 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  260 | blk.28.attn_v.weight      | Block 28 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  261 | blk.28.ffn_down.weight    | Block 28 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  262 | blk.28.ffn_gate.weight    | Block 28 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  263 | blk.28.ffn_norm.weight    | Block 28 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  264 | blk.28.ffn_up.weight      | Block 28 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.28: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_29">Block 29 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  265 | blk.29.attn_k.weight      | Block 29 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  266 | blk.29.attn_norm.weight   | Block 29 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  267 | blk.29.attn_output.weight | Block 29 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  268 | blk.29.attn_q.weight      | Block 29 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  269 | blk.29.attn_v.weight      | Block 29 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  270 | blk.29.ffn_down.weight    | Block 29 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  271 | blk.29.ffn_gate.weight    | Block 29 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  272 | blk.29.ffn_norm.weight    | Block 29 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  273 | blk.29.ffn_up.weight      | Block 29 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.29: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_30">Block 30 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  274 | blk.30.attn_k.weight      | Block 30 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  275 | blk.30.attn_norm.weight   | Block 30 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  276 | blk.30.attn_output.weight | Block 30 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  277 | blk.30.attn_q.weight      | Block 30 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  278 | blk.30.attn_v.weight      | Block 30 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | F16  |
+|  279 | blk.30.ffn_down.weight    | Block 30 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  280 | blk.30.ffn_gate.weight    | Block 30 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  281 | blk.30.ffn_norm.weight    | Block 30 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  282 | blk.30.ffn_up.weight      | Block 30 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.30: (~218M) 218112000
+- Percentage of total elements: 2.72%
+### <a name="blk_31">Block 31 Tensor Group : ~218M Elements</a>
+| T_ID | Tensor Layer Name         | Human Friendly Tensor Layer Name                | Elements        | Shape                 | Type |
+|-----:|:--------------------------|:------------------------------------------------|:----------------|:----------------------|:-----|
+|  283 | blk.31.attn_k.weight      | Block 31 Attention Key (W)                      | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q6_K |
+|  284 | blk.31.attn_norm.weight   | Block 31 Attention Normalization (W)            | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  285 | blk.31.attn_output.weight | Block 31 Attention Output (W)                   | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q8_0 |
+|  286 | blk.31.attn_q.weight      | Block 31 Attention Query (W)                    | (~17M) 16777216 |  4096 x  4096 x 1 x 1 | Q6_K |
+|  287 | blk.31.attn_v.weight      | Block 31 Attention Value (W)                    | ( ~4M)  4194304 |  4096 x  1024 x 1 x 1 | Q8_0 |
+|  288 | blk.31.ffn_down.weight    | Block 31 Feed-Forward Network "Down" (W)        | (~59M) 58720256 | 14336 x  4096 x 1 x 1 | Q8_0 |
+|  289 | blk.31.ffn_gate.weight    | Block 31 Feed-Forward Network "Gate" (W)        | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+|  290 | blk.31.ffn_norm.weight    | Block 31 Feed-Forward Network Normalization (W) | ( ~4K)     4096 |  4096 x     1 x 1 x 1 | F32  |
+|  291 | blk.31.ffn_up.weight      | Block 31 Feed-Forward Network "Up" (W)          | (~59M) 58720256 |  4096 x 14336 x 1 x 1 | Q8_0 |
+- Total elements in blk.31: (~218M) 218112000
+- Percentage of total elements: 2.72%