GGUF
conversational
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 SakuraLLM/GalTransl-v4-4B-2601:Q5_K_S
# Run inference directly in the terminal:
llama-cli -hf SakuraLLM/GalTransl-v4-4B-2601:Q5_K_S
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf SakuraLLM/GalTransl-v4-4B-2601:Q5_K_S
# Run inference directly in the terminal:
llama-cli -hf SakuraLLM/GalTransl-v4-4B-2601:Q5_K_S
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 SakuraLLM/GalTransl-v4-4B-2601:Q5_K_S
# Run inference directly in the terminal:
./llama-cli -hf SakuraLLM/GalTransl-v4-4B-2601:Q5_K_S
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 SakuraLLM/GalTransl-v4-4B-2601:Q5_K_S
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SakuraLLM/GalTransl-v4-4B-2601:Q5_K_S
Use Docker
docker model run hf.co/SakuraLLM/GalTransl-v4-4B-2601:Q5_K_S
Quick Links

GalTransl-v4-4B基于Sakura-4B-Qwen3-Base-v2
适合luna翻译器等即时翻译场景,迷你好用

6G显存用GalTransl-v4-4B-2601.gguf(Q6K量化)
4G显存用GalTransl-v4-4B-2601-Q5_K_S.gguf

建议使用Sakura_Launcher_GUI启动,上下文长度至少2048。

prompt格式同GalTransl-7B-v3.7

2026.01.28-2601:更新GalTransl-v4-4B-2601,修正输出格式不稳定的问题,并提升翻译质量。 2025.12.17-2512:初版

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GGUF
Model size
4B params
Architecture
qwen3
Hardware compatibility
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