flair: A very simple framework for state-of-the-art Natural Language Processing (NLP)
A very simple framework for state-of-the-art NLP . Developed by Zalando Research. Please enjoy reading their article Flair: State-of-the-Art Natural Language Processing (NLP).
- 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.
Paper: Contextual String Embeddings for Sequence Labeling
COLING_2018.pdf (1.7 MB)