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"
any Recommended Runtime Parameters (llama.cpp / llama-server)
thankx
mine on 32G ram with 7900XTX
llama-server.exe ^
--host 0.0.0.0 ^
--port 1337 ^
--gpu-layers all ^
--alias Qwen3.8-27B-Uncensored-Q4_K_M.JonathanColetti.gguf ^
--model \models\Qwen3.8-27B-Uncensored-Q4_K_M.JonathanColetti.gguf ^
--repeat-last-n 128 ^
--repeat-penalty 1.05 ^
--spec-draft-n-max 2 ^
--spec-draft-n-min 0 ^
--draft-p-min 0.75 ^
--spec-type draft-mtp ^
--temperature 0.2 ^
--top-p 0.9 ^
--no-webui ^
--ubatch-size 256 ^
--batch-size 256 ^
--ctx-size 81920 ^
--no-cont-batching ^
--flash-attn on ^
--fit off ^
--parallel 1 ^
--cache-type-k q4_0 ^
--cache-type-v turbo3 ^
--jinja ^
--verbose