Instructions to use WindstormLabs/translate-en-swc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-en-swc 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-en-swc")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-en-swc", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1014da6193544d0369785672f8f909a32382203a0cf9b7a237e38261757d404
- Size of remote file:
- 823 kB
- SHA256:
- d9e6a47c1b5379f63d7a78138702f77669e40271c8a8fae775e26ad32fd42ecc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.