Instructions to use tripolskypetr/Qwen3VL-Uncensored-Aggressive-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 tripolskypetr/Qwen3VL-Uncensored-Aggressive-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 tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf tripolskypetr/Qwen3VL-Uncensored-Aggressive-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 tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf tripolskypetr/Qwen3VL-Uncensored-Aggressive-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 tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf tripolskypetr/Qwen3VL-Uncensored-Aggressive-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 tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF:Q4_K_M
Use Docker
docker model run hf.co/tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF with Ollama:
ollama run hf.co/tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF:Q4_K_M
- Unsloth Studio
How to use tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF 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 tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF 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 tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF to start chatting
- Pi
How to use tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF: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": "tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use tripolskypetr/Qwen3VL-Uncensored-Aggressive-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 tripolskypetr/Qwen3VL-Uncensored-Aggressive-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 tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tripolskypetr/Qwen3VL-Uncensored-Aggressive-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 "tripolskypetr/Qwen3VL-Uncensored-Aggressive-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"
- Docker Model Runner
How to use tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF with Docker Model Runner:
docker model run hf.co/tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF:Q4_K_M
- Lemonade
How to use tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Qwen3VL-Uncensored-Aggressive-GGUF-Q4_K_M
List all available models
lemonade list
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 "tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF:" \
--custom-provider-id llama-cpp \
--custom-compatibility openai \
--custom-text-input \
--accept-risk \
--skip-healthRun OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"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"
- Downloads last month
- 1,071
4-bit
6-bit
8-bit
16-bit
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp# Start a local OpenAI-compatible server: llama serve -hf tripolskypetr/Qwen3VL-Uncensored-Aggressive-GGUF: