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| title: README | |
| emoji: π | |
| colorFrom: green | |
| colorTo: pink | |
| sdk: static | |
| pinned: false | |
| <p align="center"> | |
| <img style="vertical-align:middle" src="https://raw.githubusercontent.com/Adapter-Hub/adapters/main/docs/img/adapter-bert.png" width="80" /> | |
| </p> | |
| <h1 align="center"> | |
| <span><i>Adapters</i></span> | |
| </h1> | |
| <h3 align="center"> | |
| A Unified Library for Parameter-Efficient and Modular Transfer Learning | |
| </h3> | |
| <h3 align="center"> | |
| <a href="https://adapterhub.ml">π» Website</a> | |
| β’ | |
| <a href="https://docs.adapterhub.ml">π Documentation</a> | |
| β’ | |
| <a href="https://arxiv.org/abs/2311.11077">π Paper</a> | |
| β’ | |
| <a href="https://github.com/Adapter-Hub/adapters/tree/main/notebooks">π§ͺ Notebook Tutorials</a> | |
| </h3> | |
| _Adapters_ is an add-on library to [HuggingFace's Transformers](https://github.com/huggingface/transformers), integrating [various adapter methods](https://docs.adapterhub.ml/overview.html) into [state-of-the-art pre-trained language models](https://docs.adapterhub.ml/model_overview.html) with minimal coding overhead for training and inference. | |
| ``` | |
| pip install adapters | |
| ``` | |
| π€ Hub integration: https://docs.adapterhub.ml/huggingface_hub.html |