A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends.
Flair is:
A powerful NLP library. Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), part-of-speech tagging (PoS), sense disambiguation and classification.
Multilingual. Thanks to the Flair community, we support a rapidly growing number of languages. We also now include 'one model, many languages' taggers, i.e. single models that predict PoS or NER tags for input text in various languages.
A text embedding library. Flair has simple interfaces that allow you to use and combine different word and document embeddings, including our proposed Flair embeddings, BERT embeddings and ELMo embeddings.
A PyTorch NLP framework. Our framework builds directly on PyTorch, making it easy to train your own models and experiment with new approaches using Flair embeddings and classes.
