# HugNLP: A Unified and Comprehensive Library for Natural Language Processing

## TL;DR

HugNLP is a comprehensive library built on HuggingFace Transformers that simplifies NLP research and development by providing unified models, processors, and applications for various NLP tasks and real-world scenarios.

## Contribution

It introduces a hierarchical structure for NLP models and applications, enabling easier development and deployment of NLP algorithms with off-the-shelf and custom methods.

## Key findings

- Demonstrates effectiveness in knowledge-enhanced PLMs
- Showcases universal information extraction capabilities
- Supports low-resource NLP tasks and code understanding

## Abstract

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).