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 tinyopsec/SRA-RiskGate-4B-GGUF:
# Run inference directly in the terminal:
llama cli -hf tinyopsec/SRA-RiskGate-4B-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf tinyopsec/SRA-RiskGate-4B-GGUF:
# Run inference directly in the terminal:
llama cli -hf tinyopsec/SRA-RiskGate-4B-GGUF:
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf tinyopsec/SRA-RiskGate-4B-GGUF:
# Run inference directly in the terminal:
./build/bin/llama cli -hf tinyopsec/SRA-RiskGate-4B-GGUF:
Use Docker
docker model run hf.co/tinyopsec/SRA-RiskGate-4B-GGUF:
Quick Links

SRA-RiskGate-4B - GGUF

GGUF quantizations of sriram1983007/SRA-RiskGate-4B, produced with llama.cpp.

Available files

File Quantization
model-F16.gguf F16
model-Q8_0.gguf Q8_0
model-Q6_K.gguf Q6_K
model-Q5_K_M.gguf Q5_K_M
model-Q5_K_S.gguf Q5_K_S
model-Q5_0.gguf Q5_0
model-Q4_K_M.gguf Q4_K_M
model-Q4_K_S.gguf Q4_K_S
model-Q4_0.gguf Q4_0
model-Q3_K_L.gguf Q3_K_L
model-Q3_K_M.gguf Q3_K_M
model-Q3_K_S.gguf Q3_K_S
model-Q2_K.gguf Q2_K

Usage

With llama.cpp:

./llama-cli -m model-Q4_K_M.gguf -p "Your prompt" -n 256

License

Apache 2.0, inherited from the base model.

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Model size
4B params
Architecture
qwen3
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