Instructions to use Sefaria/he_subref_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use Sefaria/he_subref_ner with spaCy:
!pip install https://huggingface.co/Sefaria/he_subref_ner/resolve/main/he_subref_ner-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("he_subref_ner") # Importing as module. import he_subref_ner nlp = he_subref_ner.load() - Notebooks
- Google Colab
- Kaggle
Download vocab/strings.json from Sefaria/he_subref_ner: direct link, hf CLI and curl.
- Browser
- Download file 16.2 MB
-
https://huggingface.co/Sefaria/he_subref_ner/resolve/main/vocab/strings.json
- Command line
-
hf download hf://Sefaria/he_subref_ner/vocab/strings.json
-
curl -L -o strings.json https://huggingface.co/Sefaria/he_subref_ner/resolve/main/vocab/strings.json
16.2 MB
- Xet hash:
- df24b2617f03138d577a0ccc195c36e65ad30df06a429b5ac7e05f45e7124cff
- Size of remote file:
- 16.2 MB
- SHA256:
- bacb47e1488e9f01046dac7b7b9262b734ad0e21e9fc1a5d6ac72f47e7275d90
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.