Instructions to use Fmirra/gpt2-python-function with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fmirra/gpt2-python-function with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Fmirra/gpt2-python-function")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Fmirra/gpt2-python-function") model = AutoModelForCausalLM.from_pretrained("Fmirra/gpt2-python-function", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Fmirra/gpt2-python-function with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Fmirra/gpt2-python-function" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Fmirra/gpt2-python-function", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Fmirra/gpt2-python-function
- SGLang
How to use Fmirra/gpt2-python-function 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 "Fmirra/gpt2-python-function" \ --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": "Fmirra/gpt2-python-function", "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 "Fmirra/gpt2-python-function" \ --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": "Fmirra/gpt2-python-function", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Fmirra/gpt2-python-function with Docker Model Runner:
docker model run hf.co/Fmirra/gpt2-python-function
Download model.safetensors from Fmirra/gpt2-python-function: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/Fmirra/gpt2-python-function/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://Fmirra/gpt2-python-function@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Fmirra/gpt2-python-function/resolve/refs%2Fpr%2F1/model.safetensors
498 MB
- Xet hash:
- 6c6841b05d20af3cb9793f9ee843b0ec545867ae8c94b1fb49e455eb40bbe439
- Size of remote file:
- 498 MB
- SHA256:
- 496300c99688910357f37ef6f232b8e075b555b24d41b37f6de4c048320d99ce
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