Instructions to use WindyWord/translate-ve-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-ve-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-ve-es")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-ve-es", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1af01e62b8af49e0844964e2b916f05eec63a3121c80e4a1c2131c05e5cdf27d
- Size of remote file:
- 843 kB
- SHA256:
- 6b18118edb9e1daf68e85ae0ba955af0d6719559f1945ef1ab401cf018a1c1c8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.