How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf qiyue0726/neko-gemma-3-270m-it:F16_GEMMA
# Run inference directly in the terminal:
llama-cli -hf qiyue0726/neko-gemma-3-270m-it:F16_GEMMA
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf qiyue0726/neko-gemma-3-270m-it:F16_GEMMA
# Run inference directly in the terminal:
llama-cli -hf qiyue0726/neko-gemma-3-270m-it:F16_GEMMA
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 qiyue0726/neko-gemma-3-270m-it:F16_GEMMA
# Run inference directly in the terminal:
./llama-cli -hf qiyue0726/neko-gemma-3-270m-it:F16_GEMMA
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 qiyue0726/neko-gemma-3-270m-it:F16_GEMMA
# Run inference directly in the terminal:
./build/bin/llama-cli -hf qiyue0726/neko-gemma-3-270m-it:F16_GEMMA
Use Docker
docker model run hf.co/qiyue0726/neko-gemma-3-270m-it:F16_GEMMA
Quick Links

训练设备: Win11 系统,AMD 9070,Rocm7.1

Dataset: 沐雪猫娘化](https://modelscope.cn/datasets/himzhzx/muice-dataset-train.catgirl)

基础模型: Gemma-3-270m-it

f32 量化效果:

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