Instructions to use WindyWord/translate-es-ve with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-es-ve 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-es-ve")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-es-ve", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40abd55eb6edfd4b3e13a3e8a7e089cefb2a038a5f7febbed42bf85c313fcb60
- Size of remote file:
- 75 MB
- SHA256:
- 84f4c8a9ce8cc3df003395bd2cd19894b02254e80d4795a6ac787aad38ab15b5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.