Instructions to use hjianganthony/en_nerry_rel_tok2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use hjianganthony/en_nerry_rel_tok2vec with spaCy:
!pip install https://huggingface.co/hjianganthony/en_nerry_rel_tok2vec/resolve/main/en_nerry_rel_tok2vec-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_nerry_rel_tok2vec") # Importing as module. import en_nerry_rel_tok2vec nlp = en_nerry_rel_tok2vec.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0ff628d60eaed52a38b05b12d166a5dfda24d4244cf5e3dc69a33582cdd1a0f
- Size of remote file:
- 6.01 MB
- SHA256:
- 11ed239173fae244bb7f45b227e730e8873e0cf6f8c6e8a6d20d0744861d1f46
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