Instructions to use hsengiv/en_journal_sectionize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use hsengiv/en_journal_sectionize with spaCy:
!pip install https://huggingface.co/hsengiv/en_journal_sectionize/resolve/main/en_journal_sectionize-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_journal_sectionize") # Importing as module. import en_journal_sectionize nlp = en_journal_sectionize.load() - Notebooks
- Google Colab
- Kaggle
Download textcat_multilabel/model from hsengiv/en_journal_sectionize: direct link, hf CLI and curl.
- Browser
- Download file 103 kB
-
https://huggingface.co/hsengiv/en_journal_sectionize/resolve/main/textcat_multilabel/model
- Command line
-
hf download hf://hsengiv/en_journal_sectionize/textcat_multilabel/model
-
curl -L -o model https://huggingface.co/hsengiv/en_journal_sectionize/resolve/main/textcat_multilabel/model
103 kB
This file contains binary data. It cannot be displayed, but you can still download it.