HugNLP: A Unified and Comprehensive Library for Natural Language Processing

Jianing Wang, Nuo Chen, Qiushi Sun, Wenkang Huang, Chengyu Wang +1 more
2/28/2023
cs.CL

Official code: wjn1996/HugNLP (240 stars, PyTorch, last commit 2023-08-07).

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).

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Code Implementations(1)

wjn1996/HugNLPOfficial100%
PyTorch

HugNLP is a unified and comprehensive NLP library based on HuggingFace Transformer. Please hugging for NLP now!😊 HugNLP will released to @HugAILab

24012Shell, PythonFeb 18, 20233 years ago
code-understandingdeep-learningfew-shot-learningknowledge-enhancementnatural-language-processing+6 more

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Cite this paper

@article{wang2023hugnlp,
  title  = {HugNLP: A Unified and Comprehensive Library for Natural Language Processing},
  author = {Jianing Wang and Nuo Chen and Qiushi Sun and Wenkang Huang and Chengyu Wang and Ming Gao},
  year   = {2023},
  eprint = {2302.14286},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2302.14286v1}
}

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