Instructions to use WindstormLabs/translate-es-swc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-es-swc 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-swc")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-es-swc", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0ebd67610d05da8a8474f5e8eee1f73e9691e8036b71830e794ed81f2a0d64c
- Size of remote file:
- 846 kB
- SHA256:
- 4f0ddec7340a60ba61c256d3537a0a3dbc59723474b7034ba1363574f30ffbe8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.