论文标题
EasyNLP：自然语言处理的全面且易于使用的工具包
EasyNLP: A Comprehensive and Easy-to-use Toolkit for Natural Language Processing
论文作者
论文摘要
预训练模型（PTM）的成功重塑了自然语言处理（NLP）的发展。但是，获得高性能模型并在线部署为工业从业人员并不容易。为了弥合这一差距，EasyNLP旨在使构建NLP应用程序易于构建，该应用程序支持全面的NLP算法套件。它进一步具有知识增强的预训练，知识蒸馏和对大规模PTM的少数学习功能，并为现实应用程序提供了统一的模型培训，推理和部署的统一框架。目前，EasyNLP已在阿里巴巴集团内的十个业务部门供电，并无缝集成到阿里巴巴云上的AI（PAI）产品平台。我们的EasyNLP Toolkit的源代码在GitHub（https://github.com/alibaba/easynlp）上发布。
The success of Pre-Trained Models (PTMs) has reshaped the development of Natural Language Processing (NLP). Yet, it is not easy to obtain high-performing models and deploy them online for industrial practitioners. To bridge this gap, EasyNLP is designed to make it easy to build NLP applications, which supports a comprehensive suite of NLP algorithms. It further features knowledge-enhanced pre-training, knowledge distillation and few-shot learning functionalities for large-scale PTMs, and provides a unified framework of model training, inference and deployment for real-world applications. Currently, EasyNLP has powered over ten business units within Alibaba Group and is seamlessly integrated to the Platform of AI (PAI) products on Alibaba Cloud. The source code of our EasyNLP toolkit is released at GitHub (https://github.com/alibaba/EasyNLP).
