Abstract
We present iNLTK, an open-source NLP library consisting of pre-trained language models and out-of-the-box support for Data Augmentation, Textual Similarity, Sentence Embeddings, Word Embeddings, Tokenization and Text Generation in 13 Indic Languages. By using pre-trained models from iNLTK for text classification on publicly available datasets, we significantly outperform previously reported results. On these datasets, we also show that by using pre-trained models and data augmentation from iNLTK, we can achieve more than 95% of the previous best performance by using less than 10% of the training data. iNLTK is already being widely used by the community and has 40,000+ downloads, 600+ stars and 100+ forks on GitHub. The library is available at https://github.com/goru001/inltk.- Anthology ID:
- 2020.nlposs-1.10
- Volume:
- Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS)
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Eunjeong L. Park, Masato Hagiwara, Dmitrijs Milajevs, Nelson F. Liu, Geeticka Chauhan, Liling Tan
- Venue:
- NLPOSS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 66–71
- Language:
- URL:
- https://aclanthology.org/2020.nlposs-1.10
- DOI:
- 10.18653/v1/2020.nlposs-1.10
- Cite (ACL):
- Gaurav Arora. 2020. iNLTK: Natural Language Toolkit for Indic Languages. In Proceedings of Second Workshop for NLP Open Source Software (NLP-OSS), pages 66–71, Online. Association for Computational Linguistics.
- Cite (Informal):
- iNLTK: Natural Language Toolkit for Indic Languages (Arora, NLPOSS 2020)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2020.nlposs-1.10.pdf
- Code
- goru001/inltk