AdapterHub 文档

注意

本文档基于全新的Adapters库。

基于旧版adapter-transformers库的文档可在以下地址找到：https://docs-legacy.adapterhub.ml。

AdapterHub 是一个简化适配器集成、训练和使用的框架，专为基于Transformer的语言模型设计，支持多种高效微调方法。 要查看当前已实现方法的完整列表，请参阅我们代码库中的表格。

该框架由两个主要组件组成：

Adapters

AdapterHub.ml

Hugging Face的Transformers库的扩展，用于向transformer模型添加适配器

预训练适配器模块的中央集合

目前，我们支持模型概览页面上列出的所有模型的PyTorch版本。

入门指南

适配器方法

高级

加载与共享

支持的模型

适配器相关类

贡献指南

引用

如果您在工作中使用_Adapters_，请考虑引用我们的库论文Adapters: A Unified Library for Parameter-Efficient and Modular Transfer Learning 

@inproceedings{poth-etal-2023-adapters,
   title = "Adapters: A Unified Library for Parameter-Efficient and Modular Transfer Learning",
   author = {Poth, Clifton  and
      Sterz, Hannah  and
      Paul, Indraneil  and
      Purkayastha, Sukannya  and
      Engl{\"a}nder, Leon  and
      Imhof, Timo  and
      Vuli{\'c}, Ivan  and
      Ruder, Sebastian  and
      Gurevych, Iryna  and
      Pfeiffer, Jonas},
   booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
   month = dec,
   year = "2023",
   address = "Singapore",
   publisher = "Association for Computational Linguistics",
   url = "https://aclanthology.org/2023.emnlp-demo.13",
   pages = "149--160",
}

另外，对于前身adapter-transformers、Hub基础设施以及由AdapterHub团队上传的适配器，请考虑引用我们的初始论文：AdapterHub: A Framework for Adapting Transformers

@inproceedings{pfeiffer2020AdapterHub,
   title={AdapterHub: A Framework for Adapting Transformers},
   author={Jonas Pfeiffer and
            Andreas R\"uckl\'{e} and
            Clifton Poth and
            Aishwarya Kamath and
            Ivan Vuli\'{c} and
            Sebastian Ruder and
            Kyunghyun Cho and
            Iryna Gurevych},
   booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020): Systems Demonstrations},
   year={2020},
   address = "Online",
   publisher = "Association for Computational Linguistics",
   url = "https://www.aclweb.org/anthology/2020.emnlp-demos.7",
   pages = "46--54",
}

索引和表格