HugNLP: A Unified and Comprehensive Library for Natural Language Processing
This library addresses the need for a comprehensive and user-friendly tool for NLP researchers to streamline development and experimentation, though it is incremental as it builds on existing frameworks.
The authors introduced HugNLP, a unified library for natural language processing built on HuggingFace Transformers, enabling researchers to easily use existing algorithms and develop new methods for various NLP tasks, with applications demonstrated in areas like knowledge-enhanced models and low-resource mining.
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).