Instructions to use WindstormLabs/translate-bem-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-bem-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-bem-es")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-bem-es", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fbfbc93ce28e69316fe66665da86c6dee8847216de494c7d3756784ce461b70f
- Size of remote file:
- 832 kB
- SHA256:
- a3423b4499dfd5d01424bb9a80e57c7b13c51fc054d9cf4665b99aa8a176ef61
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.