How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf iacmc85/gemma3-1b-treinado# Run inference directly in the terminal:
llama cli -hf iacmc85/gemma3-1b-treinadoUse 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 iacmc85/gemma3-1b-treinado# Run inference directly in the terminal:
./llama-cli -hf iacmc85/gemma3-1b-treinadoBuild 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 iacmc85/gemma3-1b-treinado# Run inference directly in the terminal:
./build/bin/llama-cli -hf iacmc85/gemma3-1b-treinadoUse Docker
docker model run hf.co/iacmc85/gemma3-1b-treinadoQuick Links
Gemma3:1B Treinado em 03/09/2025 com a biblioteca do Unsloth e o dataset treinamento_cau_250_geral.
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Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf iacmc85/gemma3-1b-treinado# Run inference directly in the terminal: llama cli -hf iacmc85/gemma3-1b-treinado