Translation
Transformers
Safetensors
gemma3
image-text-to-text
multilingual
text-generation-inference
Instructions to use lyf07/Translategemma-4B-it-WALAR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lyf07/Translategemma-4B-it-WALAR 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="lyf07/Translategemma-4B-it-WALAR")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("lyf07/Translategemma-4B-it-WALAR") model = AutoModelForMultimodalLM.from_pretrained("lyf07/Translategemma-4B-it-WALAR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag and library metadata
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community science team, working to improve the discoverability of models on the Hub.
I've opened this PR to add important metadata to your model card:
pipeline_tag: translation: This ensures your model is correctly categorized in the Translation section of the Hub.library_name: transformers: This enables the "Use in Transformers" button and code snippets on the model page.- Paper Link: I've updated the paper link to point to the Hugging Face paper page for better integration.
- Citation: I've added a BibTeX citation section for researchers to easily cite your work.
These changes will help more people find and use your work!
Thank you so much for your help! Really appreciate your time and effort for it!
lyf07 changed pull request status to merged