Instructions to use WindyWord/translate-ts-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/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="WindyWord/translate-ts-en")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-ts-en", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06ccd6bc3cf290cdc5429ea324eeab0a09b2ac448984d8364860308a7442d473
- Size of remote file:
- 75.7 MB
- SHA256:
- 99e57c0e6ef19613707546bf894c48618d6cb762ab1d3275505551cbef311f82
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.