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 edward56/sn92-front-fast
# Run inference directly in the terminal:
llama cli -hf edward56/sn92-front-fast
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf edward56/sn92-front-fast
# Run inference directly in the terminal:
llama cli -hf edward56/sn92-front-fast
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 edward56/sn92-front-fast
# Run inference directly in the terminal:
./llama-cli -hf edward56/sn92-front-fast
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 edward56/sn92-front-fast
# Run inference directly in the terminal:
./build/bin/llama-cli -hf edward56/sn92-front-fast
Use Docker
docker model run hf.co/edward56/sn92-front-fast
Quick Links

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

SN92 Front Fast

Quantization: Q3_K_M. See manifest.json and benchmark-541.json.

Downloads last month
4
GGUF
Model size
0.6B params
Architecture
qwen3
Hardware compatibility
Log In to add your hardware

We're not able to determine the quantization variants.

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support