In this paper, we introduce HugNLP, a unified and comprehensive library for natural language processing (NLP) with the prevalent backend of HuggingFace Transformers, which is designed for NLP researchers to easily utilize off-the-shelf algorithms and develop novel methods with user-defined models and tasks in real-world scenarios. HugNLP consists of a hierarchical structure including models, processors and applications that unifies the learning process of pre-trained language models (PLMs) on different NLP tasks. Additionally, we present some featured NLP applications to show the effectiveness of HugNLP, such as knowledge-enhanced PLMs, universal information extraction, low-resource mining, and code understanding and generation, etc. The source code will be released on GitHub (https://github.com/wjn1996/HugNLP).
HugNLP: A Unified and Comprehensive Library for Natural Language Processing
HugNLP is a unified NLP library using HuggingFace Transformers, facilitating the use of pre-trained models and development of custom tasks and applications.
- Year
- 2023
- Venue
- arXiv 2023
- Authors
- 6
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- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2302.14286ARXIV-DEFAULT
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