Instructions to use rdfez/tl_custom_spacy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use rdfez/tl_custom_spacy with spaCy:
!pip install https://huggingface.co/rdfez/tl_custom_spacy/resolve/main/tl_custom_spacy-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("tl_custom_spacy") # Importing as module. import tl_custom_spacy nlp = tl_custom_spacy.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81cecb060c2bb25a47a12e0be023fe68bd2ec65e72d0e5c5c8cbb00b23b9fc9f
- Size of remote file:
- 6.01 MB
- SHA256:
- da4f6526d610e2f416cb64fb51ad6342e8560e6e3bb797fd02af294da87a9ce3
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