Instructions to use WindyWord/translate-pag-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-pag-es 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="WindyWord/translate-pag-es")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-pag-es", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7437ded32d371a4ee9e26b593c03b9b9302638b8bf7c30b946e277e6c75800b6
- Size of remote file:
- 77 MB
- SHA256:
- 4d6a485d6b6eee6af15592a435458ec3782064b89720d690be51acc385a0c6d3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.