Instructions to use 2lains/Huihui-Step3-VL-10B-abliterated-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 2lains/Huihui-Step3-VL-10B-abliterated-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 2lains/Huihui-Step3-VL-10B-abliterated-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf 2lains/Huihui-Step3-VL-10B-abliterated-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 2lains/Huihui-Step3-VL-10B-abliterated-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf 2lains/Huihui-Step3-VL-10B-abliterated-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 2lains/Huihui-Step3-VL-10B-abliterated-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf 2lains/Huihui-Step3-VL-10B-abliterated-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 2lains/Huihui-Step3-VL-10B-abliterated-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf 2lains/Huihui-Step3-VL-10B-abliterated-GGUF:Q4_K_M
Use Docker
docker model run hf.co/2lains/Huihui-Step3-VL-10B-abliterated-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use 2lains/Huihui-Step3-VL-10B-abliterated-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "2lains/Huihui-Step3-VL-10B-abliterated-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": "2lains/Huihui-Step3-VL-10B-abliterated-GGUF", "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/2lains/Huihui-Step3-VL-10B-abliterated-GGUF:Q4_K_M
- Ollama
How to use 2lains/Huihui-Step3-VL-10B-abliterated-GGUF with Ollama:
ollama run hf.co/2lains/Huihui-Step3-VL-10B-abliterated-GGUF:Q4_K_M
- Unsloth Studio
How to use 2lains/Huihui-Step3-VL-10B-abliterated-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 2lains/Huihui-Step3-VL-10B-abliterated-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 2lains/Huihui-Step3-VL-10B-abliterated-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for 2lains/Huihui-Step3-VL-10B-abliterated-GGUF to start chatting
- Pi
How to use 2lains/Huihui-Step3-VL-10B-abliterated-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf 2lains/Huihui-Step3-VL-10B-abliterated-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": "2lains/Huihui-Step3-VL-10B-abliterated-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use 2lains/Huihui-Step3-VL-10B-abliterated-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf 2lains/Huihui-Step3-VL-10B-abliterated-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 "2lains/Huihui-Step3-VL-10B-abliterated-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 2lains/Huihui-Step3-VL-10B-abliterated-GGUF with Docker Model Runner:
docker model run hf.co/2lains/Huihui-Step3-VL-10B-abliterated-GGUF:Q4_K_M
- Lemonade
How to use 2lains/Huihui-Step3-VL-10B-abliterated-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull 2lains/Huihui-Step3-VL-10B-abliterated-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Huihui-Step3-VL-10B-abliterated-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use 2lains/Huihui-Step3-VL-10B-abliterated-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 2lains/Huihui-Step3-VL-10B-abliterated-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 2lains/Huihui-Step3-VL-10B-abliterated-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
Huihui-Step3-VL-10B-abliterated-GGUF
This repository contains GGUF quantized versions of huihui-ai/Huihui-Step3-VL-10B-abliterated.
These files allow you to run the model locally on consumer hardware (CPU and Mac/PC GPUs) using llama.cpp or other compatible inference software.
⚠️ Note on Vision Capabilities
It was only the text part that was processed, not the image part.
The abliterated model will no longer say "I can’t describe or analyze this image."
🌟 About the Original Model
The original model is an uncensored (abliterated) version of stepfun-ai/Step3-VL-10B [1].
- Refusals Removed: The text component of the model was processed using the abliteration technique (orthogonalized against refusal directions). As a result, the model will no longer reply with standard refusals like "I can't describe or analyze this image." when prompted with potentially sensitive images [1].
- Capabilities: Multimodal / Vision-Language (Image-Text-to-Text) [1].
- Language: Multilingual / Conversational [1].
Note: Only the text-generation part was abliterated; the vision encoder retains its original mapping [1].
🚀 How to Run
You can run this model using llama.cpp or UI tools based on it (such as LM Studio, Ollama, text-generation-webui, etc.).
Using llama.cpp (Command Line)
Because this is a Vision-Language Model (VLM), you must pass the multimodal projector file (--mmproj) alongside the main model to process images.
# Example command using llama-cli
./llama-cli \
-m Huihui-Step3-VL-10B-abliterated-Q4_K_M.gguf \
--mmproj Huihui-Step3-VL-10B-abliterated-mmproj-f16.gguf \
--image path/to/your/image.png \
-p "Describe this image in detail." \
-c 4096 \
-temp 0.7
Note: Please ensure you are using a recent version of llama.cpp that supports the Step3-VL architecture.
⚠️ Usage Warnings (From the Original Author)
- Risk of Sensitive or Controversial Outputs: This model's safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content [1]. Users should exercise caution and rigorously review generated outputs.
- Not Suitable for All Audiences: Due to limited content filtering, the model's outputs may be inappropriate for public settings, underage users, or applications requiring high security [1].
- Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences [1].
- Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications [1].
- No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. The authors bear no responsibility for any consequences arising from its use [1].
💖 Credits
- Original Base Model:
stepfun-ai[1] - Abliteration processing:
huihui-ai[1] - GGUF Quantization:
2lains
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Model tree for 2lains/Huihui-Step3-VL-10B-abliterated-GGUF
Base model
stepfun-ai/Step3-VL-10B-Base