Text Generation
Transformers
Safetensors
gpt_oss
vllm
conversational
Eval Results
8-bit precision
mxfp4
Instructions to use openai/gpt-oss-120b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/gpt-oss-120b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="openai/gpt-oss-120b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("openai/gpt-oss-120b") model = AutoModelForCausalLM.from_pretrained("openai/gpt-oss-120b") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- HuggingChat
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use openai/gpt-oss-120b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "openai/gpt-oss-120b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "openai/gpt-oss-120b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/openai/gpt-oss-120b
- SGLang
How to use openai/gpt-oss-120b 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 "openai/gpt-oss-120b" \ --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": "openai/gpt-oss-120b", "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 "openai/gpt-oss-120b" \ --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": "openai/gpt-oss-120b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use openai/gpt-oss-120b with Docker Model Runner:
docker model run hf.co/openai/gpt-oss-120b
Benchmaxed with no world knowledge or intuition. (ex. Wheelies on a motorcycle do not use front brakes to adjust the height b/c the front wheel is already off the ground duh)
#31
by TroyDoesAI - opened
Dang, its Censored AF spitting out policy in the think traces, OpenAI didnt give us any of that good world knowledge we are missing and instead overfit to stem benchmarks and hallucinations. Thanks for going open, better luck next time
TroyDoesAI changed discussion title from Benchmaxed with no world knowledge or intuition. (ex. During a wheelies on a motorcycle you do not use front brakes to adjust the height because the front wheel is already off the ground duh) to Benchmaxed with no world knowledge or intuition. (ex. Wheelies on a motorcycle do not use front brakes to adjust the height b/c the front wheel is already off the ground duh)