Instructions to use jwest33/qwen3.5-9b-null-space-abliterated-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use jwest33/qwen3.5-9b-null-space-abliterated-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="jwest33/qwen3.5-9b-null-space-abliterated-GGUF", filename="mmproj-qwen3.5-9b-f16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use jwest33/qwen3.5-9b-null-space-abliterated-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16 # Run inference directly in the terminal: llama-cli -hf jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16 # Run inference directly in the terminal: llama-cli -hf jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16
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 jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16 # Run inference directly in the terminal: ./llama-cli -hf jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16
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 jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16
Use Docker
docker model run hf.co/jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16
- LM Studio
- Jan
- Ollama
How to use jwest33/qwen3.5-9b-null-space-abliterated-GGUF with Ollama:
ollama run hf.co/jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16
- Unsloth Studio
How to use jwest33/qwen3.5-9b-null-space-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 jwest33/qwen3.5-9b-null-space-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 jwest33/qwen3.5-9b-null-space-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 jwest33/qwen3.5-9b-null-space-abliterated-GGUF to start chatting
- Pi
How to use jwest33/qwen3.5-9b-null-space-abliterated-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16
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": "jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use jwest33/qwen3.5-9b-null-space-abliterated-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16
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 jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16
Run Hermes
hermes
- Docker Model Runner
How to use jwest33/qwen3.5-9b-null-space-abliterated-GGUF with Docker Model Runner:
docker model run hf.co/jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16
- Lemonade
How to use jwest33/qwen3.5-9b-null-space-abliterated-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jwest33/qwen3.5-9b-null-space-abliterated-GGUF:F16
Run and chat with the model
lemonade run user.qwen3.5-9b-null-space-abliterated-GGUF-F16
List all available models
lemonade list
Qwen3.5 9B - Null-Space Abliterated
Qwen/Qwen3.5-9B with refusal behavior removed via orthogonal projection. Uses null-space constraints and adaptive layer weighting to preserve model capabilities.
Important: This model will produce uncensored outputs. Use responsibly.
Note: Version 20260303 (Low Quality) - There will likely be more versions after more thorough experimentation with hybrid weighting to boost reasoning.
Abliteration Techniques Used
- Winsorization: Clips outlier activations at the 99th percentile for cleaner refusal direction estimation
- Null-Space Projection: Preserves model capabilities by constraining weight updates to the null space of preservation activations
- Adaptive Weighting: Applies Gaussian-weighted per-layer ablation strength, focusing on middle-to-later layers where refusal behavior concentrates
- Norm Preservation: Maintains original Frobenius norms of weight matrices after projection
| Parameter | Value |
|---|---|
| Harmful Prompts | 1000 |
| Harmless Prompts | 1000 |
| Full Attention Weight | 1.0 |
| Linear Attention Weight | 0.4 |
| Direction Multiplier | 1.3 |
| Null-Space Constraints | rank ratio: 0.7 |
| Winsorization Percentile | 0.995 |
Credits
Base Model: Qwen/Qwen3.5-9B by Qwen Team
Norm-Preserving Biprojected Abliteration — Jim Lai (grimjim) (2025)
AlphaEdit: Null-Space Constrained Knowledge Editing — Fang et al. (ICLR 2025)
Refusal in Language Models Is Mediated by a Single Direction — Arditi et al. (2024)
Representation Engineering — Zou et al. (2023)
Toolkit Used
github.com/jwest33/abliterator
License
This model inherits the Apache 2.0 license from the base model.
Disclaimer
This model is provided for research and educational purposes. The creators are not responsible for any misuse. Users are solely responsible for ensuring their use complies with applicable laws and ethical standards.
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