Instructions to use refactai/codify_3b_multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use refactai/codify_3b_multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="refactai/codify_3b_multi", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("refactai/codify_3b_multi", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use refactai/codify_3b_multi with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "refactai/codify_3b_multi" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "refactai/codify_3b_multi", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/refactai/codify_3b_multi
- SGLang
How to use refactai/codify_3b_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 "refactai/codify_3b_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": "refactai/codify_3b_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 "refactai/codify_3b_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": "refactai/codify_3b_multi", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use refactai/codify_3b_multi with Docker Model Runner:
docker model run hf.co/refactai/codify_3b_multi
- Xet hash:
- ff9b8a7ba92b94b0688c145a48b73e47d277cb3435b2c8525b65b50bbc85ae1a
- Size of remote file:
- 13.1 MB
- SHA256:
- 1e487bec9464f014472c47b31d5b493e387c1868411e28b423a7c08a4fd2e661
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.