Top NER Methods 2024: GliNER & spaCy 🚀

GLiNER: https://github.com/urchade/GLiNER
Gliner spaCy: https://github.com/theirstory/gliner-spacy

The GLiNER repository is a generalist model for Named Entity Recognition (NER), designed to extract a wide range of entity types from text. It represents an advanced approach to recognizing various entities in text data.

The gliner-spacy repository provides a SpaCy wrapper for GLiNER, facilitating the integration of GLiNER's advanced NER capabilities into the SpaCy environment. This wrapper supports customizable settings for processing text, such as chunk size, specific entity labels, and output style for entity recognition results.

In this tutorial, I dive into the basics of the gliner-spacy repository, showing you how to seamlessly integrate GLiNER's robust NER capabilities with SpaCy's versatile NLP environment. Whether you're new to natural language processing or looking to enhance your projects with state-of-the-art entity recognition, this video is your go-to guide. Plus, get a clear understanding of zero-shot learning and its application in zero-shot NER. Don't forget to like, share, and subscribe for more insightful tutorials on NLP and AI technologies!


Join this channel to get access to perks:
https://www.youtube.com/channel/UC5vr5PwcXiKX_-6NTteAlXw/join

If you enjoy this video, please subscribe.
✅Be my Patron: https://www.patreon.com/WJBMattingly
✅PayPal: https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=AZ73QW52SUX8N&currency_code=USD&source=url

If there's a specific video you would like to see or a tutorial series, let me know in the comments and I will try and make it.

If you liked this video, check out www.PythonHumanities.com, where I have Coding Exercises, Lessons, on-site Python shells where you can experiment with code, and a text version of the material discussed here.
You can follow me at:
https://twitter.com/wjb_mattingly