Instructions to use andreids/en_ner_sender with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use andreids/en_ner_sender with spaCy:
!pip install https://huggingface.co/andreids/en_ner_sender/resolve/main/en_ner_sender-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_ner_sender") # Importing as module. import en_ner_sender nlp = en_ner_sender.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ee4966d494c5779e91dd0c4a3628c8df687c7c8e4b8c247e4e163f51087ece8
- Size of remote file:
- 6.24 MB
- SHA256:
- 7b2fbd70910e0f563a980c811ce4c64d19ea02ec5ba09de3d55c00cffb7870fd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.