FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP
Alan Akbik, Tanja Bergmann, Duncan Blythe, Kashif Rasul, Stefan Schweter, Roland Vollgraf
Abstract
We present FLAIR, an NLP framework designed to facilitate training and distribution of state-of-the-art sequence labeling, text classification and language models. The core idea of the framework is to present a simple, unified interface for conceptually very different types of word and document embeddings. This effectively hides all embedding-specific engineering complexity and allows researchers to “mix and match” various embeddings with little effort. The framework also implements standard model training and hyperparameter selection routines, as well as a data fetching module that can download publicly available NLP datasets and convert them into data structures for quick set up of experiments. Finally, FLAIR also ships with a “model zoo” of pre-trained models to allow researchers to use state-of-the-art NLP models in their applications. This paper gives an overview of the framework and its functionality. The framework is available on GitHub at https://github.com/zalandoresearch/flair .- Anthology ID:
- N19-4010
- Volume:
- Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations)
- Month:
- June
- Year:
- 2019
- Address:
- Minneapolis, Minnesota
- Editors:
- Waleed Ammar, Annie Louis, Nasrin Mostafazadeh
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 54–59
- Language:
- URL:
- https://aclanthology.org/N19-4010
- DOI:
- 10.18653/v1/N19-4010
- Cite (ACL):
- Alan Akbik, Tanja Bergmann, Duncan Blythe, Kashif Rasul, Stefan Schweter, and Roland Vollgraf. 2019. FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations), pages 54–59, Minneapolis, Minnesota. Association for Computational Linguistics.
- Cite (Informal):
- FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP (Akbik et al., NAACL 2019)
- PDF:
- https://preview.aclanthology.org/naacl-24-ws-corrections/N19-4010.pdf
- Code
- zalandoresearch/flair
- Data
- CoNLL 2003, IMDb Movie Reviews