Instructions to use WindstormLabs/translate-et-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-et-de 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-et-de")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-et-de", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 507355f5db37122d93694ef6b82b6a6e19506eb74c3f726a4da6e66aa288842a
- Size of remote file:
- 823 kB
- SHA256:
- eb028e7d1749418cd1829c330fa386a74a30ee5e74aad1847fe7d6a838304cde
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.