Instructions to use WindyWord/translate-en-tdt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-en-tdt 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="WindyWord/translate-en-tdt")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-en-tdt", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d005374096ff117df287b3e3a21da450bc915f6bfb34f014774f2eb58ee9ecbc
- Size of remote file:
- 63.6 MB
- SHA256:
- 4f05b0de63a7776c9eccc9388069efe4f780378a11d14e1568cc41c085148087
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.