Instructions to use WindstormLabs/translate-mfe-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-mfe-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="WindstormLabs/translate-mfe-es")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-mfe-es", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8625ff784c383a552c72f189824832b9cedc4cff681f5393cc6c266de75ff32a
- Size of remote file:
- 843 kB
- SHA256:
- fcec6b130f008ba4af2befd31a1742fe35135f1ac8f2975db90ea0a372885e1c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.