Instructions to use MatteoKhan/CodeLlama-7B-Merged-Python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MatteoKhan/CodeLlama-7B-Merged-Python with Transformers:

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

pipe = pipeline("text-generation", model="MatteoKhan/CodeLlama-7B-Merged-Python")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("MatteoKhan/CodeLlama-7B-Merged-Python")
model = AutoModelForMultimodalLM.from_pretrained("MatteoKhan/CodeLlama-7B-Merged-Python")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use MatteoKhan/CodeLlama-7B-Merged-Python with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/MatteoKhan/CodeLlama-7B-Merged-Python

SGLang

How to use MatteoKhan/CodeLlama-7B-Merged-Python 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 "MatteoKhan/CodeLlama-7B-Merged-Python" \
    --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": "MatteoKhan/CodeLlama-7B-Merged-Python",
		"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 "MatteoKhan/CodeLlama-7B-Merged-Python" \
        --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": "MatteoKhan/CodeLlama-7B-Merged-Python",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use MatteoKhan/CodeLlama-7B-Merged-Python with Docker Model Runner:
```
docker model run hf.co/MatteoKhan/CodeLlama-7B-Merged-Python
```

MatteoKhan commited on Mar 4, 2025

Commit

d113c4e

verified ·

1 Parent(s): 21a5e2c

Update README.md

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README.md +0 -6

README.md CHANGED Viewed

@@ -93,12 +93,6 @@ outputs = model.generate(**inputs, max_length=200)
 response = tokenizer.decode(outputs[0], skip_special_tokens=True)
 print(response)
 ```
-## 📜 Citation & References
-If you use **CodeLlama-Hybrid-7B** in your research, please cite the parent models:
-**📝 CodeLlama**
 📩 **Feedback & Contact**: Reach out via [Hugging Face](https://huggingface.co/MatteoKhan).
 🎉 **Happy Coding!** 🚀

 response = tokenizer.decode(outputs[0], skip_special_tokens=True)
 print(response)
 ```
 📩 **Feedback & Contact**: Reach out via [Hugging Face](https://huggingface.co/MatteoKhan).
 🎉 **Happy Coding!** 🚀