Instructions to use anilb/translategemma-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use anilb/translategemma-gguf with 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 anilb/translategemma-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf anilb/translategemma-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf anilb/translategemma-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf anilb/translategemma-gguf:Q4_K_M

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 anilb/translategemma-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf anilb/translategemma-gguf:Q4_K_M

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 anilb/translategemma-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf anilb/translategemma-gguf:Q4_K_M

Use Docker

docker model run hf.co/anilb/translategemma-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use anilb/translategemma-gguf with Ollama:
```
ollama run hf.co/anilb/translategemma-gguf:Q4_K_M
```

Unsloth Studio

How to use anilb/translategemma-gguf 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 anilb/translategemma-gguf 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 anilb/translategemma-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for anilb/translategemma-gguf to start chatting

Docker Model Runner
How to use anilb/translategemma-gguf with Docker Model Runner:
```
docker model run hf.co/anilb/translategemma-gguf:Q4_K_M
```

Lemonade

How to use anilb/translategemma-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull anilb/translategemma-gguf:Q4_K_M

Run and chat with the model

lemonade run user.translategemma-gguf-Q4_K_M

List all available models

lemonade list

Atomic Chat

TranslateGemma GGUF (Q4_K_M)

Q4_K_M quantized derivatives of Google's official TranslateGemma weights, re-hosted here for use as a bundled, fully-local translation engine (run via llama.cpp).

Files

File	Source model	Quant
`translategemma-4b-it.Q4_K_M.gguf`	`google/translategemma-4b-it`	Q4_K_M
`translategemma-12b-it.Q4_K_M.gguf`	`google/translategemma-12b-it`	Q4_K_M

Provenance & modification notice

These files are quantized (Q4_K_M) from the official google/translategemma-* weights. They are modified (quantized) copies of the original model, not the original weights. The GGUF conversions were obtained from the community mradermacher static-quant repositories (which document the same official Google source) and re-hosted here unchanged.

License

Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms

Downloads last month: 193

GGUF

Model size

12B params

Architecture

gemma3

Hardware compatibility

4-bit

Model tree for anilb/translategemma-gguf

Base model

google/translategemma-12b-it

Quantized

(25)

this model