Introduction to Flair for NLP: A Simple yet Powerful State-of-the-Art NLP Library
Introduction
Last couple of years have been incredible for Natural Language Processing (NLP) as a domain! We have seen multiple breakthroughs – ULMFiT, ELMo, Facebook’s PyText, Google’s BERT, among many others. These have rapidly accelerated the state-of-the-art research in NLP (and language modeling, in particular).
We can now predict the next sentence, given a sequence of preceding words.
What’s even more important is that machines are now beginning to understand the key element that had eluded them for long.
Context! Understanding context has broken down barriers that had prevented NLP techniques making headway before. And today, we are going to talk about one such library – Flair.
Until now, the words were either represented as a sparse matrix or as word embeddings such as GLoVe, Bert and ELMo, and the results have been pretty impressive. But, there’s always room for improvement and Flair is willing to stand up to it.