Instructions to use WindyWord/translate-lu-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-lu-en 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-en")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-lu-en", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49c4d637d5e4d09e1842a25934beca8096221446b35e3981d11e0a2c4b58c362
- Size of remote file:
- 829 kB
- SHA256:
- d58f151eb7dda15a34ce78517d7129bdf2f5d65318b6a22bd7f583b24fe36978
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.