Instructions to use codeparrot/codeparrot-small-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codeparrot/codeparrot-small-multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="codeparrot/codeparrot-small-multi")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("codeparrot/codeparrot-small-multi") model = AutoModelForCausalLM.from_pretrained("codeparrot/codeparrot-small-multi") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use codeparrot/codeparrot-small-multi with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "codeparrot/codeparrot-small-multi" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "codeparrot/codeparrot-small-multi", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/codeparrot/codeparrot-small-multi
- SGLang
How to use codeparrot/codeparrot-small-multi 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 "codeparrot/codeparrot-small-multi" \ --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": "codeparrot/codeparrot-small-multi", "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 "codeparrot/codeparrot-small-multi" \ --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": "codeparrot/codeparrot-small-multi", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use codeparrot/codeparrot-small-multi with Docker Model Runner:
docker model run hf.co/codeparrot/codeparrot-small-multi
| temperature 0.2: {'pass@1': 0.027439024390243896, 'pass@10': 0.041979293327556816, 'pass@100': 0.04268292682926801} | |
| temperature 0.8: {'pass@1': 0.013262195121951224, 'pass@10': 0.04670902438514701, 'pass@100': 0.0899080946922357} | |
| best: {'pass@1': 2.74% , 'pass@10': 4.67 , 'pass@100': 8.99%} |