Instructions to use IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF", dtype="auto", device_map="auto")

llama-cpp-python

How to use IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF",
	filename="EdgeRunner-Baby_Phoenix-1B-IQ4_XS.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS
# Run inference directly in the terminal:
llama cli -hf IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS
# Run inference directly in the terminal:
llama cli -hf IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS

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 IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS
# Run inference directly in the terminal:
./llama-cli -hf IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS

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 IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS
# Run inference directly in the terminal:
./build/bin/llama-cli -hf IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS

Use Docker

docker model run hf.co/IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS

LM Studio
Jan
Ollama
How to use IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF with Ollama:
```
ollama run hf.co/IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS
```

Unsloth Studio

How to use IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-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 IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-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 IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF to start chatting

How to use IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF with Docker Model Runner:
```
docker model run hf.co/IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS
```

Lemonade

How to use IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF:IQ4_XS

Run and chat with the model

lemonade run user.EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF-IQ4_XS

List all available models

lemonade list

IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF

A small functional edge model which leads the field in excellance on devices and in swarms.

This model was converted to GGUF format from Youlln/ECE-PRYMMAL-YL-1B-SLERP-V2 using llama.cpp Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

Downloads last month: 5

GGUF

Model size

2B params

Architecture

qwen2

Hardware compatibility

4-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF

Base model

Youlln/ECE-PRYMMAL-YL-1B-SLERP-V2

Quantized

(3)

this model

IntelligentEstate
/

EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF

IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF

Use with llama.cpp

Model tree for IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF

Dataset used to train IntelligentEstate/EdgeRunner-Baby_Phoenix-1B-IQ4_XS-GGUF