Instructions to use filbench/tl_xlm_roberta_transition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use filbench/tl_xlm_roberta_transition with spaCy:
!pip install https://huggingface.co/filbench/tl_xlm_roberta_transition/resolve/main/tl_xlm_roberta_transition-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("tl_xlm_roberta_transition") # Importing as module. import tl_xlm_roberta_transition nlp = tl_xlm_roberta_transition.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88d786308b2d88a5699d7e52f4f629c3261ac85a8774ce91bc4a13cf71d1a144
- Size of remote file:
- 1.34 MB
- SHA256:
- f0ee233074513d0d18a9eb530a82b4a988e7f03bcd0e9d569cf27d1496d5cb14
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