HugNLP: A Unified and Comprehensive Library for Natural Language Processing

被引：4

作者：

Wang, Jianing ^{[1
]}

Chen, Nuo ^{[1
]}

Sun, Qiushi ^{[2
]}

Huang, Wenkang ^{[3
]}

Wang, Chengyu ^{[4
]}

Gao, Ming ^{[1
]}

机构：

[1] East China Normal Univ, Shanghai, Peoples R China

[2] Natl Univ Singapore, Singapore, Singapore

[3] Ant Grp, Shanghai, Peoples R China

[4] Alibaba Grp, Hangzhou, Peoples R China

来源：

PROCEEDINGS OF THE 32ND ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, CIKM 2023 | 2023年

关键词：

Natural Language Processing; Pre-trained Language Models; Deep Learning Framework;

D O I：

10.1145/3583780.3614742

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we introduce HugNLP, a unified and comprehensive library for natural language processing (NLP) with the prevalent backend of Hugging Face 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/HugAILab/HugNLP).

引用

页码：5111 / 5116

页数：6

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