Text Generation
Transformers
Safetensors
starcoder2
trl
sft
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use panf9/python-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use panf9/python-code with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="panf9/python-code")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("panf9/python-code") model = AutoModelForCausalLM.from_pretrained("panf9/python-code") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use panf9/python-code with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "panf9/python-code" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "panf9/python-code", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/panf9/python-code
- SGLang
How to use panf9/python-code 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 "panf9/python-code" \ --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": "panf9/python-code", "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 "panf9/python-code" \ --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": "panf9/python-code", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use panf9/python-code with Docker Model Runner:
docker model run hf.co/panf9/python-code
- Xet hash:
- c3694d60bc93f587d6010b2c0a9f914e502abe6bfc8e7ffc00d108d6f7731054
- Size of remote file:
- 1.94 GB
- SHA256:
- c68b962ac7bd99d5b5d193225381b059cde0eb2777b279aec4f0dd4bb5ce8c57
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