Instructions to use SakuraLLM/GalTransl-v4-4B-2601 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SakuraLLM/GalTransl-v4-4B-2601 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="SakuraLLM/GalTransl-v4-4B-2601",
	filename="Galtransl-v4-4B-2601-Q5_K_S.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use SakuraLLM/GalTransl-v4-4B-2601 with 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

LM Studio
Jan
Ollama
How to use SakuraLLM/GalTransl-v4-4B-2601 with Ollama:
```
ollama run hf.co/SakuraLLM/GalTransl-v4-4B-2601:Q5_K_S
```

Unsloth Studio new

How to use SakuraLLM/GalTransl-v4-4B-2601 with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for SakuraLLM/GalTransl-v4-4B-2601 to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for SakuraLLM/GalTransl-v4-4B-2601 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for SakuraLLM/GalTransl-v4-4B-2601 to start chatting

Docker Model Runner
How to use SakuraLLM/GalTransl-v4-4B-2601 with Docker Model Runner:
```
docker model run hf.co/SakuraLLM/GalTransl-v4-4B-2601:Q5_K_S
```

Lemonade

How to use SakuraLLM/GalTransl-v4-4B-2601 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SakuraLLM/GalTransl-v4-4B-2601:Q5_K_S

Run and chat with the model

lemonade run user.GalTransl-v4-4B-2601-Q5_K_S

List all available models

lemonade list

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

Downloads last month: 2,214

GGUF

Model size

4B params

Architecture

qwen3

Hardware compatibility

5-bit

View +1 variant

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