Instructions to use WindyWord/translate-en-pis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-en-pis 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-en-pis")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-en-pis", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3276b782fc508a860e29056c4c0054a26c8ce9d17e40f63ef19c184162a8dfcb
- Size of remote file:
- 816 kB
- SHA256:
- 33a54526e005b1ae5f08e5bee2df2d477536ebe192158775b9562f4781be0e96
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