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
| {"time": 1755040255.0687401, "step": null, "level": "INFO", "msg": "Config loaded", "data": {"config_path": "configs/full.yaml"}} | |
| {"time": 1755040255.068824, "step": null, "level": "INFO", "msg": "Loading dataset ...", "data": {}} | |
| {"time": 1755040257.6130784, "step": null, "level": "INFO", "msg": "Dataset loaded", "data": {"size": 2}} | |
| {"time": 1755040257.6131446, "step": null, "level": "INFO", "msg": "Loading model/tokenizer ...", "data": {}} | |
| {"time": 1755040264.1002383, "step": null, "level": "INFO", "msg": "Model loaded", "data": {"trainable_params": 15040512}} | |
| {"time": 1755040264.3870833, "step": null, "level": "INFO", "msg": "Starting training ...", "data": {}} | |
| {"time": 1755040527.7214618, "step": null, "level": "INFO", "msg": "Config loaded", "data": {"config_path": "configs/full.yaml"}} | |
| {"time": 1755040527.7215579, "step": null, "level": "INFO", "msg": "Loading dataset ...", "data": {}} | |
| {"time": 1755040529.3749201, "step": null, "level": "INFO", "msg": "Dataset loaded", "data": {"size": 1140}} | |
| {"time": 1755040529.3750272, "step": null, "level": "INFO", "msg": "Loading model/tokenizer ...", "data": {}} | |
| {"time": 1755040535.6129575, "step": null, "level": "INFO", "msg": "Model loaded", "data": {"trainable_params": 15040512}} | |
| {"time": 1755040536.956728, "step": null, "level": "INFO", "msg": "Starting training ...", "data": {}} | |
| {"time": 1755044254.8595893, "step": null, "level": "INFO", "msg": "Training complete", "data": {"train_runtime": 3717.3139, "train_samples_per_second": 0.43, "train_steps_per_second": 0.027, "total_flos": 6.825417425085542e+16, "train_loss": 0.7833267974853516}} | |