Text Generation
Transformers
Safetensors
PEFT
lora
bigcodebench
gpt-oss
code
causal-lm
conversational
Instructions to use unlimitedbytes/gptoss-bigcodebench-20b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unlimitedbytes/gptoss-bigcodebench-20b-lora with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="unlimitedbytes/gptoss-bigcodebench-20b-lora") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unlimitedbytes/gptoss-bigcodebench-20b-lora", dtype="auto") - PEFT
How to use unlimitedbytes/gptoss-bigcodebench-20b-lora with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use unlimitedbytes/gptoss-bigcodebench-20b-lora with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "unlimitedbytes/gptoss-bigcodebench-20b-lora" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "unlimitedbytes/gptoss-bigcodebench-20b-lora", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/unlimitedbytes/gptoss-bigcodebench-20b-lora
- SGLang
How to use unlimitedbytes/gptoss-bigcodebench-20b-lora 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 "unlimitedbytes/gptoss-bigcodebench-20b-lora" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "unlimitedbytes/gptoss-bigcodebench-20b-lora", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "unlimitedbytes/gptoss-bigcodebench-20b-lora" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "unlimitedbytes/gptoss-bigcodebench-20b-lora", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use unlimitedbytes/gptoss-bigcodebench-20b-lora with Docker Model Runner:
docker model run hf.co/unlimitedbytes/gptoss-bigcodebench-20b-lora
- Xet hash:
- 5243971418114d8547c1b58e36bf1ee1f191ac48ab74b4f41b3e79291b22161c
- Size of remote file:
- 6.16 kB
- SHA256:
- 14cb0dfbc65a20b75f73e74187abf2046eed01f1c1d00e7138c25b610fc1cfa1
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