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:
- 196a2d833da7d331b9944f1ecfa26af19b48fef432039eba04054f75e360acaf
- Size of remote file:
- 75.6 MB
- SHA256:
- 9a7d0075681e4ccf0eaf43a6225bd389cfcec0a9858d1923848928cf70ce6564
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.