Instructions to use WindstormLabs/translate-sv-he with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-sv-he 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-sv-he")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-sv-he", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3680f17042f1a99c257ddd874be57bfc7cae1528c5aa376ce24a3972fac6cf27
- Size of remote file:
- 78.6 MB
- SHA256:
- 2669f66f5b1df7997a36b4bda0fae1ab0f66e290f48c6bdceaa8ce14a3b0a347
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.