Instructions to use HuggingBelto/gpt-oss-20b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use HuggingBelto/gpt-oss-20b with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="HuggingBelto/gpt-oss-20b", filename="gpt-oss-20b.Q8_0.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use HuggingBelto/gpt-oss-20b with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf HuggingBelto/gpt-oss-20b:Q8_0 # Run inference directly in the terminal: llama-cli -hf HuggingBelto/gpt-oss-20b:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf HuggingBelto/gpt-oss-20b:Q8_0 # Run inference directly in the terminal: llama-cli -hf HuggingBelto/gpt-oss-20b:Q8_0
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf HuggingBelto/gpt-oss-20b:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf HuggingBelto/gpt-oss-20b:Q8_0
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf HuggingBelto/gpt-oss-20b:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf HuggingBelto/gpt-oss-20b:Q8_0
Use Docker
docker model run hf.co/HuggingBelto/gpt-oss-20b:Q8_0
- LM Studio
- Jan
- vLLM
How to use HuggingBelto/gpt-oss-20b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "HuggingBelto/gpt-oss-20b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "HuggingBelto/gpt-oss-20b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/HuggingBelto/gpt-oss-20b:Q8_0
- Ollama
How to use HuggingBelto/gpt-oss-20b with Ollama:
ollama run hf.co/HuggingBelto/gpt-oss-20b:Q8_0
- Unsloth Studio new
How to use HuggingBelto/gpt-oss-20b with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for HuggingBelto/gpt-oss-20b to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for HuggingBelto/gpt-oss-20b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for HuggingBelto/gpt-oss-20b to start chatting
- Pi new
How to use HuggingBelto/gpt-oss-20b with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf HuggingBelto/gpt-oss-20b:Q8_0
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "HuggingBelto/gpt-oss-20b:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use HuggingBelto/gpt-oss-20b with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf HuggingBelto/gpt-oss-20b:Q8_0
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default HuggingBelto/gpt-oss-20b:Q8_0
Run Hermes
hermes
- Docker Model Runner
How to use HuggingBelto/gpt-oss-20b with Docker Model Runner:
docker model run hf.co/HuggingBelto/gpt-oss-20b:Q8_0
- Lemonade
How to use HuggingBelto/gpt-oss-20b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull HuggingBelto/gpt-oss-20b:Q8_0
Run and chat with the model
lemonade run user.gpt-oss-20b-Q8_0
List all available models
lemonade list
π© Report: Illegal or restricted content
Open model being sold, scam.
Its the sale of the format - not the model.
You didn't invent the GGUF format, nor the quantization methods used, you're trying to scam with open-source technology and models.
I can literally find tons of GPT-OSS 20B GGUF quantizations just by searching in this site, all the way down to IQ1 quants.
Either you're really dumb, or you're really good at acting like so.
Go and train your own model from scratch, that you can monetize, not some 8-bit quantization everyone can do at their home for free.