Summary

Hugging Face is a hugely-popular, extremely well supported library to create, share and use transformer-based machine learning models for a several common, text classification and analysis tasks. It isn't limited to analyzing text, but offers several powerful, model agnostic APIs for cutting edge NLP tasks like question answering, zero-shot (no training) text classification, text summarization and more. Many NLP research groups publish versions of their models compatible with Hugging Face, so you can easily plug and play different pre-trained models without needing to rewrite your code. They also have a great online course that will let you start harnessing the incredible power of transformers through Hugging Face's library without needing to become an expert on machine learning.