Instructions to use ChaoticNeutrals/Lunar_10.7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ChaoticNeutrals/Lunar_10.7B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="ChaoticNeutrals/Lunar_10.7B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ChaoticNeutrals/Lunar_10.7B")
model = AutoModelForCausalLM.from_pretrained("ChaoticNeutrals/Lunar_10.7B")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ChaoticNeutrals/Lunar_10.7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ChaoticNeutrals/Lunar_10.7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ChaoticNeutrals/Lunar_10.7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ChaoticNeutrals/Lunar_10.7B

SGLang

How to use ChaoticNeutrals/Lunar_10.7B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "ChaoticNeutrals/Lunar_10.7B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ChaoticNeutrals/Lunar_10.7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "ChaoticNeutrals/Lunar_10.7B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ChaoticNeutrals/Lunar_10.7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ChaoticNeutrals/Lunar_10.7B with Docker Model Runner:
```
docker model run hf.co/ChaoticNeutrals/Lunar_10.7B
```

This model consists of a finetuned model of my own SLERP merged with this model: https://huggingface.co/Sao10K/Sensualize-Solar-10.7B created by https://huggingface.co/Sao10K

Lunar was produced by a variety of methods for the purpose of being a companion bot capable of intimacy as well as conversation.

GGUF here: https://huggingface.co/jeiku/Lunar_10.7B_GGUF

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	67.25
AI2 Reasoning Challenge (25-Shot)	65.87
HellaSwag (10-Shot)	84.85
MMLU (5-Shot)	64.23
TruthfulQA (0-shot)	53.51
Winogrande (5-shot)	81.37
GSM8k (5-shot)	53.68

Downloads last month: 63

Safetensors

Model size

11B params

Tensor type

BF16

Evaluation results

normalized accuracy on AI2 Reasoning Challenge (25-Shot)
test set Open LLM Leaderboard

65.870
normalized accuracy on HellaSwag (10-Shot)
validation set Open LLM Leaderboard

84.850
accuracy on MMLU (5-Shot)
test set Open LLM Leaderboard

64.230
mc2 on TruthfulQA (0-shot)
validation set Open LLM Leaderboard

53.510
accuracy on Winogrande (5-shot)
validation set Open LLM Leaderboard

81.370
accuracy on GSM8k (5-shot)
test set Open LLM Leaderboard

53.680