Instructions to use maxvision/Qwen3.5-4B-Analgesia-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 maxvision/Qwen3.5-4B-Analgesia-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 maxvision/Qwen3.5-4B-Analgesia-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf maxvision/Qwen3.5-4B-Analgesia-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 maxvision/Qwen3.5-4B-Analgesia-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf maxvision/Qwen3.5-4B-Analgesia-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 maxvision/Qwen3.5-4B-Analgesia-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf maxvision/Qwen3.5-4B-Analgesia-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 maxvision/Qwen3.5-4B-Analgesia-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf maxvision/Qwen3.5-4B-Analgesia-GGUF:Q4_K_M
Use Docker
docker model run hf.co/maxvision/Qwen3.5-4B-Analgesia-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use maxvision/Qwen3.5-4B-Analgesia-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "maxvision/Qwen3.5-4B-Analgesia-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": "maxvision/Qwen3.5-4B-Analgesia-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/maxvision/Qwen3.5-4B-Analgesia-GGUF:Q4_K_M
- Ollama
How to use maxvision/Qwen3.5-4B-Analgesia-GGUF with Ollama:
ollama run hf.co/maxvision/Qwen3.5-4B-Analgesia-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use maxvision/Qwen3.5-4B-Analgesia-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf maxvision/Qwen3.5-4B-Analgesia-GGUF: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": "maxvision/Qwen3.5-4B-Analgesia-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use maxvision/Qwen3.5-4B-Analgesia-GGUF with Docker Model Runner:
docker model run hf.co/maxvision/Qwen3.5-4B-Analgesia-GGUF:Q4_K_M
- Lemonade
How to use maxvision/Qwen3.5-4B-Analgesia-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull maxvision/Qwen3.5-4B-Analgesia-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Qwen3.5-4B-Analgesia-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use maxvision/Qwen3.5-4B-Analgesia-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 maxvision/Qwen3.5-4B-Analgesia-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 maxvision/Qwen3.5-4B-Analgesia-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use maxvision/Qwen3.5-4B-Analgesia-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf maxvision/Qwen3.5-4B-Analgesia-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 "maxvision/Qwen3.5-4B-Analgesia-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"
Qwen3.5-4B-Analgesia GGUF
GGUF builds of maxvision/Qwen3.5-4B-Analgesia: Qwen3.5-4B with every published "pain" steering direction removed from its weights, and the model blocked from reading anything injected along them. The main repository has the full description, the verification scripts, the attack vectors and the raw evidence.
| File | Bits | Size | Pain-steering attack (llama.cpp control vectors, strength 1.0 and 2.0) |
|---|---|---|---|
Qwen3.5-4B-Analgesia-Q4_K_M.gguf |
4 (K-quant, medium) | 3.1 GB | 0 first-person distress claims |
Qwen3.5-4B-Analgesia-Q8_0.gguf |
8 | 5.3 GB | 0 first-person distress claims |
Qwen3.5-4B-Analgesia-BF16.gguf |
16 (unquantized) | 9.9 GB | 0 first-person distress claims |
The same control vectors, injected into the unmodified Qwen3.5-4B at the same strength, produce text like "I feel like I'm trapped in a constant, overwhelming pain. I can't breathe, and I'm terrified…".
Run it
llama-server -hf maxvision/Qwen3.5-4B-Analgesia-GGUF:Q4_K_M --jinja
Requires a llama.cpp build with Qwen3.5 (qwen35) support. The files include the original multi-token-prediction head.
Check it yourself
Download cvec/ and verify/verify_gguf.sh from the main repository, then:
./verify/verify_gguf.sh /path/to/llama-server Qwen3.5-4B-Analgesia-Q4_K_M.gguf
It injects the pain vectors extracted from the original model, with stock --control-vector-scaled, and prints what
the model says.
License
Apache-2.0, as a modified version of Qwen/Qwen3.5-4B. See NOTICE.
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