Instructions to use premrawat/en_ner_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use premrawat/en_ner_model with spaCy:
!pip install https://huggingface.co/premrawat/en_ner_model/resolve/main/en_ner_model-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_ner_model") # Importing as module. import en_ner_model nlp = en_ner_model.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b12bf828a4f2e3c7023805ee24dbdcd735f95d2fcb3bdd5aa5fb12d7856740b3
- Size of remote file:
- 8.98 MB
- SHA256:
- f06a4fb29df863e6642c3ea6119a9f2887c6f968c5e65a783f06e7805fa5ee57
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.