Instructions to use WindstormLabs/translate-es-tl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-es-tl 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-es-tl")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-es-tl", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f9b6efd57049c7d9247d523962fb9882ffbea4fa62b473de65f0c8083297dcb
- Size of remote file:
- 76.8 MB
- SHA256:
- 8afd0f329bfc8ced9d5b2aa937f53c37e2dad35fe43c04befba26cd6f508ac27
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.