Instructions to use solidrust/Luna-7B-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use solidrust/Luna-7B-AWQ with Transformers:

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

pipe = pipeline("text-generation", model="solidrust/Luna-7B-AWQ")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("solidrust/Luna-7B-AWQ")
model = AutoModelForCausalLM.from_pretrained("solidrust/Luna-7B-AWQ")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use solidrust/Luna-7B-AWQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "solidrust/Luna-7B-AWQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "solidrust/Luna-7B-AWQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/solidrust/Luna-7B-AWQ

SGLang

How to use solidrust/Luna-7B-AWQ 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 "solidrust/Luna-7B-AWQ" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "solidrust/Luna-7B-AWQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "solidrust/Luna-7B-AWQ" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "solidrust/Luna-7B-AWQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use solidrust/Luna-7B-AWQ with Docker Model Runner:
```
docker model run hf.co/solidrust/Luna-7B-AWQ
```

Suparious commited on Mar 6, 2024

Commit

2dab442

verified ·

1 Parent(s): e80910b

update link to model creator

Browse files

Files changed (1) hide show

README.md +2 -2

README.md CHANGED Viewed

@@ -106,7 +106,7 @@ model-index:
       url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jeiku/Luna_7B
       name: Open LLM Leaderboard
 library_name: transformers
-model_creator: ResplendentAI
 model_name: Luna-7B
 model_type: mistral
 pipeline_tag: text-generation
@@ -126,7 +126,7 @@ quantized_by: Suparious
 ---
 # jeiku/Luna-7B AWQ
-- Model creator: [jeiku](https://huggingface.co/ResplendentAI)
 - Original model: [Luna-7B](https://huggingface.co/jeiku/Luna_7B)
 ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/626dfb8786671a29c715f8a9/wWVQIvXTN5JLRL6f7K6S0.jpeg)

       url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jeiku/Luna_7B
       name: Open LLM Leaderboard
 library_name: transformers
+model_creator: jeiku
 model_name: Luna-7B
 model_type: mistral
 pipeline_tag: text-generation
 ---
 # jeiku/Luna-7B AWQ
+- Model creator: [jeiku](https://huggingface.co/jeiku)
 - Original model: [Luna-7B](https://huggingface.co/jeiku/Luna_7B)
 ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/626dfb8786671a29c715f8a9/wWVQIvXTN5JLRL6f7K6S0.jpeg)