Instructions to use WindyWord/translate-sg-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-sg-es 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-sg-es")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-sg-es", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46071b37ee78e90c0bcf6ca7c8edaba4028cd137a022386524eebcc167632df4
- Size of remote file:
- 533 kB
- SHA256:
- 083ea89546536ea63752d8fbc4a4d3d5dbf1d58e2a66308cf02c2849f874ab8b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.