Instructions to use WindstormLabs/translate-ts-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-ts-en 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-ts-en")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-ts-en", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a0c79c5e0f11eb67f8bfca69ea492a255e8d5d12f0d53b5d5cf1f0c935be509
- Size of remote file:
- 827 kB
- SHA256:
- 4a8990b262cb8808895bf9345cdd92bd61563061b0db9886524f60149c430a36
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.