Instructions to use Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ", filename="Qwen3.6-27B-PRISM-PRO-DQ.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 Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ # Run inference directly in the terminal: llama-cli -hf Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ # Run inference directly in the terminal: llama-cli -hf Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ
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 Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ # Run inference directly in the terminal: ./llama-cli -hf Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ
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 Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ # Run inference directly in the terminal: ./build/bin/llama-cli -hf Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ
Use Docker
docker model run hf.co/Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ
- LM Studio
- Jan
- vLLM
How to use Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ
- Ollama
How to use Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ with Ollama:
ollama run hf.co/Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ
- Unsloth Studio new
How to use Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ 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 Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ 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 Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ to start chatting
- Pi new
How to use Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ
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": "Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ
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 Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ
Run Hermes
hermes
- Docker Model Runner
How to use Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ with Docker Model Runner:
docker model run hf.co/Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ
- Lemonade
How to use Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Ex0bit/Qwen3.6-27B-PRISM-PRO-DQ
Run and chat with the model
lemonade run user.Qwen3.6-27B-PRISM-PRO-DQ-{{QUANT_TAG}}List all available models
lemonade list
Loading Failure on LM Studio 04.13
I've been running the uncensored HauHauCS version of Qwen3.6:27B up to now and wanted to give this version a try on the same system but it keeps failing to load. Settings exactly the same, just won't run at the moment. Anyone else having difficulty running this? Any help or advice. It should run the same as my other version I would have thought
lmstudio doesnt support mtp yet