Instructions to use WindyWord/translate-wls-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-wls-fr 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-wls-fr")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-wls-fr", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3461ceb039128e88a252ea98988506197ec89a9c4c264d97a0e6612236419dae
- Size of remote file:
- 67.2 MB
- SHA256:
- d585ea6cc2f47fc8a5e148720dead4e73dd7b9115a057d20e4aa32206681e733
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.