Instructions to use google/translategemma-4b-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/translategemma-4b-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="google/translategemma-4b-it")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("google/translategemma-4b-it", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use google/translategemma-4b-it with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "google/translategemma-4b-it" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "google/translategemma-4b-it", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/google/translategemma-4b-it
- SGLang
How to use google/translategemma-4b-it with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "google/translategemma-4b-it" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "google/translategemma-4b-it", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "google/translategemma-4b-it" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "google/translategemma-4b-it", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use google/translategemma-4b-it with Docker Model Runner:
docker model run hf.co/google/translategemma-4b-it
Passing context to the model
How to pass the context to the model along with the input text? What should be the structure of messages?
Hi @Mahendranath -
Thanks for reaching out to us!
For google/translategemma-4b-it , the model expects a structured message format with only user and assistant roles and a fixed schema. Each user message must include a single content entry with fields such as type where the property where the value must be either text or image, source_lang_code, target_lang_code.
The content list entry should provide either a url property, if the entry's type is image, from which the image will be loaded or a text property, if the entry's type is text, containing only the text to translate.
Example:
messages = [
{
"role": "user",
"content": [
{
"type": "text",
"source_lang_code": "cs",
"target_lang_code": "de-DE",
"text": "V nejhorším případě i k prasknutí čočky.",
}
],
}
]