Instructions to use UBC-NLP/IndT5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UBC-NLP/IndT5 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("UBC-NLP/IndT5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36420843b93503c698416bbc5d50774b32634d8462c182a681375688288d9c9e
- Size of remote file:
- 2.07 MB
- SHA256:
- f5866e92ed31084afbbd84f68db17021422071aad5f001a5164540d8ad9b2b4d
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