Instructions to use pltobing/translategemma-4b-it-Q8_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use pltobing/translategemma-4b-it-Q8_0-GGUF with Transformers:

# Use a pipeline as a high-level helper
# Warning: Pipeline type "translation" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# 'pip install "transformers<5.0.0'
from transformers import pipeline

pipe = pipeline("translation", model="pltobing/translategemma-4b-it-Q8_0-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("pltobing/translategemma-4b-it-Q8_0-GGUF", dtype="auto")

llama-cpp-python

How to use pltobing/translategemma-4b-it-Q8_0-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="pltobing/translategemma-4b-it-Q8_0-GGUF",
	filename="translategemma-4b-it-q8_0.gguf",
)

llm.create_chat_completion(
	messages = "\"Меня зовут Вольфганг и я живу в Берлине\""
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use pltobing/translategemma-4b-it-Q8_0-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama-cli -hf pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama-cli -hf pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0

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 pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0

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 pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0

Use Docker

docker model run hf.co/pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0

LM Studio
Jan
Ollama
How to use pltobing/translategemma-4b-it-Q8_0-GGUF with Ollama:
```
ollama run hf.co/pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0
```

Unsloth Studio

How to use pltobing/translategemma-4b-it-Q8_0-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 pltobing/translategemma-4b-it-Q8_0-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 pltobing/translategemma-4b-it-Q8_0-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for pltobing/translategemma-4b-it-Q8_0-GGUF to start chatting

Docker Model Runner
How to use pltobing/translategemma-4b-it-Q8_0-GGUF with Docker Model Runner:
```
docker model run hf.co/pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0
```

Lemonade

How to use pltobing/translategemma-4b-it-Q8_0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull pltobing/translategemma-4b-it-Q8_0-GGUF:Q8_0

Run and chat with the model

lemonade run user.translategemma-4b-it-Q8_0-GGUF-Q8_0

List all available models

lemonade list

Access Gemma on Hugging Face

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

To access Gemma on Hugging Face, you’re required to review and agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging Face and click below. Requests are processed immediately.

TranslateGemma GGUF Q8_0

Device: CPU/GPU
Language: 55 languages (see model origin details)
Speed: ~10 token/s on m8a.xlarge (5th Gen AMD EPYC 9R45 CPU)
Model origin (see for model details): https://huggingface.co/google/translategemma-4b-it

By: Patrick Lumbantobing

Copyright@VertoX-AI

Downloads last month: 6

GGUF

Model size

4B params

Architecture

gemma3

Hardware compatibility

8-bit

Model tree for pltobing/translategemma-4b-it-Q8_0-GGUF

Base model

google/translategemma-4b-it

Quantized

(32)

this model

Collection including pltobing/translategemma-4b-it-Q8_0-GGUF

Streaming ST

Collection

Streaming speech translation models and frameworks • 3 items • Updated Mar 28

Access Gemma on Hugging Face

TranslateGemma GGUF Q8_0

Device: CPU/GPU

Language: 55 languages (see model origin details)

Speed: ~10 token/s on m8a.xlarge (5th Gen AMD EPYC 9R45 CPU)

Model origin (see for model details): https://huggingface.co/google/translategemma-4b-it

By: Patrick Lumbantobing

Copyright@VertoX-AI

Model tree for pltobing/translategemma-4b-it-Q8_0-GGUF

Collection including pltobing/translategemma-4b-it-Q8_0-GGUF