Instructions to use HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive 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 HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive 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 HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive:Q4_K_M # Run inference directly in the terminal: llama cli -hf HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive:Q4_K_M # Run inference directly in the terminal: llama cli -hf HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive: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 HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive: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 HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive:Q4_K_M
Use Docker
docker model run hf.co/HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive:Q4_K_M
- Ollama
How to use HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive with Ollama:
ollama run hf.co/HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive:Q4_K_M
- Unsloth Desktop
- Pi
How to use HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive: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": "HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive with Docker Model Runner:
docker model run hf.co/HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive:Q4_K_M
- Lemonade
How to use HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive:Q4_K_M
Run and chat with the model
lemonade run user.Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive: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 HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive: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 "HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive: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"
It does not work with Hermes
Model loaded correctly, but it can not use the tools, it does not complete any task, it can generate simple text , but no tools
- low quantization
- tool support not declared somewhere
- missing jinja template for correct tool handling
so does it or does it not?
it's working for me -
exec llama-server
-hf HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
--host 0.0.0.0
--port 8090
--ctx-size 251072
--n-gpu-layers 99
--flash-attn on
--cache-type-k q4_0
--cache-type-v q4_0
--parallel 1
--cont-batching
--jinja
--alias "qwen-uncensored"
--api-key 1234567890
--no-webui
-ub 512
--no-mmap
One question: which one is better, Ollama or Llama.cpp ..??
One question: which one is better, Ollama or Llama.cpp ..??
bro ollama is just a slow wrapper around llama
Model loaded correctly, but it can not use the tools, it does not complete any task, it can generate simple text , but no tools
Qwens 3.5 and 3.6 have an issue with tool calls due to training, can be fixed with template tweaks. Wait for llama to fix it, PR is in.