Instructions to use WindyWord/translate-lu-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-lu-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-lu-es")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-lu-es", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 553d46f81c791c9a16f89841d758f2b43e0e232fb5edd6b1482b712ae61f7a13
- Size of remote file:
- 829 kB
- SHA256:
- 62009bf6d2954966733b7e44c1de9cdb81935d3a2687147d5cb7138227bc620b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.