Instructions to use WindstormLabs/translate-en-gl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-en-gl 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="WindstormLabs/translate-en-gl")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-en-gl", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5d51b849e948a24c889a799b0e250454a5ca218e09e2934b0f902cb28e4e653
- Size of remote file:
- 800 kB
- SHA256:
- e74ae9fed111b0c5537370a2a68d99998277c28dc45a4fc242e1bcafc5d2f6ff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.