Instructions to use WindstormLabs/translate-st-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-st-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-st-es")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-st-es", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6891741b38660d278e0f44f73b1a21a249f03f53d3f9b61db2423655867bb833
- Size of remote file:
- 77.1 MB
- SHA256:
- bb98bbc3ce7f238c1ebdc79da914cfc185336dec2b149c68fb9eeb0bb8394951
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.