How to use from
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 faradailab/guard-granite:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf faradailab/guard-granite:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf faradailab/guard-granite:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf faradailab/guard-granite: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 faradailab/guard-granite:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf faradailab/guard-granite: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 faradailab/guard-granite:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf faradailab/guard-granite:Q4_K_M
Use Docker
docker model run hf.co/faradailab/guard-granite:Q4_K_M
Quick Links

FaradAiGuard Granite Guardian 2.0B Security SLM 🛡️

Enterprise compliance and data loss prevention (DLP) inspector. Part of the FaradAiGuard Security SLM Factory.

🚀 Instant Ollama Run

Run this model directly without local configuration or compilation:

ollama run hf.co/faradailab/guard-granite:latest

⚙️ Model Details

  • Distribution: Hugging Face Hub (faradailab/guard-granite)
  • Format: GGUF (guard-granite.Q4_K_M.gguf)
  • System Prompt & Strict JSON Grammar: Pre-configured via Modelfile.
  • Repository: https://github.com/kurtfi/FaradAiGuard

📐 Strict Output Schema (GBNF Grammar)

FaradAiGuard models return strictly validated JSON:

{
  "verdict": "ALLOW" | "BLOCK",
  "risk_score": 0.0 - 1.0,
  "reason": "Brief technical security explanation",
  "cwe": "CWE-ID or empty string"
}
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Model size
3B params
Architecture
granite
Hardware compatibility
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4-bit

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