Instructions to use premrawat/en_ner_skills with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use premrawat/en_ner_skills with spaCy:
!pip install https://huggingface.co/premrawat/en_ner_skills/resolve/main/en_ner_skills-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_ner_skills") # Importing as module. import en_ner_skills nlp = en_ner_skills.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38c83f00f47743ca84dedf5cf62089c213f5bc72378f91faa454ce84b8d2e387
- Size of remote file:
- 8.98 MB
- SHA256:
- 60e0d18381a8e3a930b23130cd0c1b5e90a0380961f27388745bd0cbcf9a1cd6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.