Instructions to use HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive", filename="Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-BF16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive:Q4_K_M # Run inference directly in the terminal: llama-cli -hf HauhauCS/Qwen3VL-8B-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-server -hf HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive:Q4_K_M # Run inference directly in the terminal: llama-cli -hf HauhauCS/Qwen3VL-8B-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/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf HauhauCS/Qwen3VL-8B-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/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive:Q4_K_M
Use Docker
docker model run hf.co/HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive with Ollama:
ollama run hf.co/HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive:Q4_K_M
- Unsloth Studio new
How to use HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive 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 HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive 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 HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive to start chatting
- Pi new
How to use HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive:Q4_K_M
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": "HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use HauhauCS/Qwen3VL-8B-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-server -hf HauhauCS/Qwen3VL-8B-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/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive with Docker Model Runner:
docker model run hf.co/HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive:Q4_K_M
- Lemonade
How to use HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull HauhauCS/Qwen3VL-8B-Uncensored-HauhauCS-Aggressive:Q4_K_M
Run and chat with the model
lemonade run user.Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-Q4_K_M
List all available models
lemonade list
Qwen3VL-8B-Uncensored-HauhauCS-Aggressive
Join the Discord for updates, roadmaps, projects, or just to chat.
Qwen3VL-8B uncensored by HauhauCS.
About
No changes to datasets or capabilities. Fully functional, 100% of what the original authors intended - just without the refusals.
These are meant to be the best lossless uncensored models out there.
Aggressive vs Balanced
This is the Aggressive variant with stronger uncensoring. Use this when the Balanced variant refuses too much.
For agentic coding and reliability-critical tasks, use the Balanced variant instead.
Downloads
| File | Quant | Size |
|---|---|---|
| Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-BF16.gguf | BF16 | 16 GB |
| Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-Q8_0.gguf | Q8_0 | 8.2 GB |
| Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-Q6_K.gguf | Q6_K | 6.3 GB |
| Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-Q4_K_M.gguf | Q4_K_M | 4.7 GB |
| Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-mmproj-f16.gguf | mmproj | 1.1 GB |
Specs
- 8B parameters
- 256K context
- Vision-language model (requires mmproj file for image input)
- Based on Qwen3-VL-8B
Usage
Works with llama.cpp, LM Studio, koboldcpp, etc.
For vision capabilities, load both the main model and the mmproj file.
llama.cpp example:
./llama-cli -m Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-Q4_K_M.gguf \
--mmproj Qwen3VL-8B-Uncensored-HauhauCS-Aggressive-mmproj-f16.gguf \
--image your_image.jpg \
-p "Describe this image"
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