Instructions to use WindstormLabs/translate-en-st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-en-st 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-st")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-en-st", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9321f0635e86c3807466c291380e1076522a6f7703bd156e7d93ad9ba1e2d03
- Size of remote file:
- 823 kB
- SHA256:
- ae68167072df23ed4bf5f1be29fc0a0797873d0e4f46d0898f6a8800753ccf9e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.