Instructions to use hexitlabs/vigil-models 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 hexitlabs/vigil-models 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 hexitlabs/vigil-models # Run inference directly in the terminal: llama cli -hf hexitlabs/vigil-models
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf hexitlabs/vigil-models # Run inference directly in the terminal: llama cli -hf hexitlabs/vigil-models
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 hexitlabs/vigil-models # Run inference directly in the terminal: ./llama-cli -hf hexitlabs/vigil-models
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 hexitlabs/vigil-models # Run inference directly in the terminal: ./build/bin/llama-cli -hf hexitlabs/vigil-models
Use Docker
docker model run hf.co/hexitlabs/vigil-models
- LM Studio
- Jan
- Ollama
How to use hexitlabs/vigil-models with Ollama:
ollama run hf.co/hexitlabs/vigil-models
- Unsloth Desktop
- Pi
How to use hexitlabs/vigil-models with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf hexitlabs/vigil-models
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": "hexitlabs/vigil-models" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use hexitlabs/vigil-models with Docker Model Runner:
docker model run hf.co/hexitlabs/vigil-models
- Lemonade
How to use hexitlabs/vigil-models with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull hexitlabs/vigil-models
Run and chat with the model
lemonade run user.vigil-models-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use hexitlabs/vigil-models with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf hexitlabs/vigil-models
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 hexitlabs/vigil-models
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use hexitlabs/vigil-models with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf hexitlabs/vigil-models
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 "hexitlabs/vigil-models" \ --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"
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Check out the documentation for more information.
Vigil Models
Fine-tuned safety models for the Vigil AI agent safety framework.
Models
vigil-v1 (4.4 GB)
- Base: Qwen 2.5 7B (Q4_K_M quantization)
- Purpose: Full safety classification model โ prompt injection, jailbreaks, data exfiltration, unsafe tool calls
- Usage:
ollama pull hexitlabs/vigil-v1(if published to Ollama registry) or download GGUF below
vigil-lite (986 MB)
- Base: Qwen 2.5 1.5B (Q4_K_M quantization)
- Purpose: Lightweight safety model for edge/CPU deployment โ 5x smaller, 2.5x faster, 93.3% accuracy
- Usage:
ollama pull hexitlabs/vigil-lite(if published to Ollama registry) or download GGUF below
Files
vigil-v1.ggufโ Full 7B model weightsvigil-lite.ggufโ Lite 1.5B model weightsModelfile-v1โ Ollama Modelfile for vigil-v1Modelfile-liteโ Ollama Modelfile for vigil-lite
Quick Start (Ollama)
# Download the GGUF file, then:
ollama create vigil-v1 -f Modelfile-v1
ollama create vigil-lite -f Modelfile-lite
Built by HexIT Labs
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Hardware compatibility
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We're not able to determine the quantization variants.
Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐ Ask for provider support