Instructions to use JonathanColetti/Qwen3.8-27B-Uncensored-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use JonathanColetti/Qwen3.8-27B-Uncensored-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M
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 JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M
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 JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M
Use Docker
docker model run hf.co/JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use JonathanColetti/Qwen3.8-27B-Uncensored-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "JonathanColetti/Qwen3.8-27B-Uncensored-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "JonathanColetti/Qwen3.8-27B-Uncensored-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M
- Ollama
How to use JonathanColetti/Qwen3.8-27B-Uncensored-GGUF with Ollama:
ollama run hf.co/JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use JonathanColetti/Qwen3.8-27B-Uncensored-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use JonathanColetti/Qwen3.8-27B-Uncensored-GGUF with Docker Model Runner:
docker model run hf.co/JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M
- Lemonade
How to use JonathanColetti/Qwen3.8-27B-Uncensored-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Qwen3.8-27B-Uncensored-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use JonathanColetti/Qwen3.8-27B-Uncensored-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M
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 JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use JonathanColetti/Qwen3.8-27B-Uncensored-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "JonathanColetti/Qwen3.8-27B-Uncensored-GGUF:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Could you please upload the BF16 vision model? Thanks!
I’m not sure why my ComfyUI can’t recognize the F16 vision model, but the language model works fine.
Im not sure if thats the correct solution but nonetheless, I did it: https://huggingface.co/JonathanColetti/Qwen3.8-27B-Uncensored-GGUF/blob/main/Qwen3.8-27B-Uncensored-vision-bf16.gguf let me know if it works
I tried it, but no luck — both the BF16 and F16 vision models are still being recognized as checkpoint models rather than vision models in ComfyUI. That said, I've managed to get someone else's ComfyUI Qwen3.8 27B vision model working, so I'm all set now. Thanks anyway for your help!
Hi, I ended up getting it work. I have a new section in the model card (https://huggingface.co/JonathanColetti/Qwen3.8-27B-Uncensored-GGUF#comfyui) that explains it. I had to first define the custom module here ComfyUI/custom_nodes/ComfyUI-QwenVL/custom_models.json then in that json put this key: "mmproj_file": "Qwen3.8-27B-Uncensored-vision-f16.gguf", because the filename did not start with mmproj-. However, now it starts with the prefix mmproj so you should not have to do that. Anyway thanks for bringing this issue to my attention @yah4