Instructions to use bartowski/Magicoder-S-CL-7B-exl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use bartowski/Magicoder-S-CL-7B-exl2 with Transformers:

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

pipe = pipeline("text-generation", model="bartowski/Magicoder-S-CL-7B-exl2")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("bartowski/Magicoder-S-CL-7B-exl2", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use bartowski/Magicoder-S-CL-7B-exl2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bartowski/Magicoder-S-CL-7B-exl2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "bartowski/Magicoder-S-CL-7B-exl2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/bartowski/Magicoder-S-CL-7B-exl2

SGLang

How to use bartowski/Magicoder-S-CL-7B-exl2 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 "bartowski/Magicoder-S-CL-7B-exl2" \
    --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": "bartowski/Magicoder-S-CL-7B-exl2",
		"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 "bartowski/Magicoder-S-CL-7B-exl2" \
        --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": "bartowski/Magicoder-S-CL-7B-exl2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use bartowski/Magicoder-S-CL-7B-exl2 with Docker Model Runner:
```
docker model run hf.co/bartowski/Magicoder-S-CL-7B-exl2
```

bartowski commited on Dec 5, 2023

Commit

a220d92

1 Parent(s): 7b9b0be

Add 4.0 link

Browse files

Files changed (1) hide show

README.md +2 -0

README.md CHANGED Viewed

@@ -20,6 +20,8 @@ Default arguments used except when the bits per weight is above 6.0, at that poi
 Original model: https://huggingface.co/ise-uiuc/Magicoder-S-CL-7B
 <a href="https://huggingface.co/bartowski/Magicoder-S-CL-7B-exl2/tree/5_0">5.0 bits per weight</a>
 <a href="https://huggingface.co/bartowski/Magicoder-S-CL-7B-exl2/tree/6_0">6.0 bits per weight</a>

 Original model: https://huggingface.co/ise-uiuc/Magicoder-S-CL-7B
+<a href="https://huggingface.co/bartowski/Magicoder-S-CL-7B-exl2/tree/4_0">4.0 bits per weight</a>
 <a href="https://huggingface.co/bartowski/Magicoder-S-CL-7B-exl2/tree/5_0">5.0 bits per weight</a>
 <a href="https://huggingface.co/bartowski/Magicoder-S-CL-7B-exl2/tree/6_0">6.0 bits per weight</a>