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توضیحات

A friendly fork of HuggingFace's Transformers, adding Adapters to PyTorch language models

ویژگی	مقدار
سیستم عامل	-
نام فایل	cody-adapter-transformers-3.0.1
نام	cody-adapter-transformers
نسخه کتابخانه	3.0.1
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, Hannah Sterz, based on work by the HuggingFace team and community
ایمیل نویسنده	pfeiffer@ukp.tu-darmstadt.de
آدرس صفحه اصلی	https://github.com/adapter-hub/adapter-transformers
آدرس اینترنتی	https://pypi.org/project/cody-adapter-transformers/
مجوز	Apache

<p align="center"> <img style="vertical-align:middle" src="https://raw.githubusercontent.com/Adapter-Hub/adapter-transformers/master/adapter_docs/logo.png" /> </p> <h1 align="center"> <span>adapter-transformers</span> </h1> <h3 align="center"> A friendly fork of HuggingFace's <i>Transformers</i>, adding Adapters to PyTorch language models </h3> ![Tests](https://github.com/Adapter-Hub/adapter-transformers/workflows/Tests/badge.svg) [![GitHub](https://img.shields.io/github/license/adapter-hub/adapter-transformers.svg?color=blue)](https://github.com/adapter-hub/adapter-transformers/blob/master/LICENSE) [![PyPI](https://img.shields.io/pypi/v/adapter-transformers)](https://pypi.org/project/adapter-transformers/) `adapter-transformers` is an extension of [HuggingFace's Transformers](https://github.com/huggingface/transformers) library, integrating adapters into state-of-the-art language models by incorporating **[AdapterHub](https://adapterhub.ml)**, a central repository for pre-trained adapter modules. _💡 Important: This library can be used as a drop-in replacement for HuggingFace Transformers and regularly synchronizes new upstream changes. Thus, most files in this repository are direct copies from the HuggingFace Transformers source, modified only with changes required for the adapter implementations._ ## Installation `adapter-transformers` currently supports **Python 3.6+** and **PyTorch 1.3.1+**. After [installing PyTorch](https://pytorch.org/get-started/locally/), you can install `adapter-transformers` from PyPI ... ``` pip install -U adapter-transformers ``` ... or from source by cloning the repository: ``` git clone https://github.com/adapter-hub/adapter-transformers.git cd adapter-transformers pip install . ``` ## Getting Started HuggingFace's great documentation on getting started with _Transformers_ can be found [here](https://huggingface.co/transformers/index.html). `adapter-transformers` is fully compatible with _Transformers_. To get started with adapters, refer to these locations: - **[Colab notebook tutorials](https://github.com/Adapter-Hub/adapter-transformers/tree/master/notebooks)**, a series notebooks providing an introduction to all the main concepts of (adapter-)transformers and AdapterHub - **https://docs.adapterhub.ml**, our documentation on training and using adapters with _adapter-transformers_ - **https://adapterhub.ml** to explore available pre-trained adapter modules and share your own adapters - **[Examples folder](https://github.com/Adapter-Hub/adapter-transformers/tree/master/examples/pytorch)** of this repository containing HuggingFace's example training scripts, many adapted for training adapters ## Implemented Methods Currently, adapter-transformers integrates all architectures and methods listed below: | Method | Paper(s) | Quick Links | | --- | --- | --- | | Bottleneck adapters | [Houlsby et al. (2019)](https://arxiv.org/pdf/1902.00751.pdf)<br> [Bapna and Firat (2019)](https://arxiv.org/pdf/1909.08478.pdf) | [Quickstart](https://docs.adapterhub.ml/quickstart.html), [Notebook](https://colab.research.google.com/github/Adapter-Hub/adapter-transformers/blob/master/notebooks/01_Adapter_Training.ipynb) | | AdapterFusion | [Pfeiffer et al. (2021)](https://aclanthology.org/2021.eacl-main.39.pdf) | [Docs: Training](https://docs.adapterhub.ml/training.html#train-adapterfusion), [Notebook](https://colab.research.google.com/github/Adapter-Hub/adapter-transformers/blob/master/notebooks/03_Adapter_Fusion.ipynb) | | MAD-X,<br> Invertible adapters | [Pfeiffer et al. (2020)](https://aclanthology.org/2020.emnlp-main.617/) | [Notebook](https://colab.research.google.com/github/Adapter-Hub/adapter-transformers/blob/master/notebooks/04_Cross_Lingual_Transfer.ipynb) | | AdapterDrop | [Rücklé et al. (2021)](https://arxiv.org/pdf/2010.11918.pdf) | [Notebook](https://colab.research.google.com/github/Adapter-Hub/adapter-transformers/blob/master/notebooks/05_Adapter_Drop_Training.ipynb) | | MAD-X 2.0,<br> Embedding training | [Pfeiffer et al. (2021)](https://arxiv.org/pdf/2012.15562.pdf) | [Docs: Embeddings](https://docs.adapterhub.ml/embeddings.html), [Notebook](https://colab.research.google.com/github/Adapter-Hub/adapter-transformers/blob/master/notebooks/08_NER_Wikiann.ipynb) | | Prefix Tuning | [Li and Liang (2021)](https://arxiv.org/pdf/2101.00190.pdf) | [Docs](https://docs.adapterhub.ml/overview.html#prefix-tuning) | | Parallel adapters,<br> Mix-and-Match adapters | [He et al. (2021)](https://arxiv.org/pdf/2110.04366.pdf) | [Docs](https://docs.adapterhub.ml/overview.html#combinations-mix-and-match-adapters) | | Compacter | [Mahabadi et al. (2021)](https://arxiv.org/pdf/2106.04647.pdf) | [Docs](https://docs.adapterhub.ml/overview.html#compacter) | ## Supported Models We currently support the PyTorch versions of all models listed on the **[Model Overview](https://docs.adapterhub.ml/model_overview.html) page** in our documentation. ## Citation If you use this library for your work, please consider citing our paper [AdapterHub: A Framework for Adapting Transformers](https://arxiv.org/abs/2007.07779): ``` @inproceedings{pfeiffer2020AdapterHub, title={AdapterHub: A Framework for Adapting Transformers}, author={Pfeiffer, Jonas and R{\"u}ckl{\'e}, Andreas and Poth, Clifton and Kamath, Aishwarya and Vuli{\'c}, Ivan and Ruder, Sebastian and Cho, Kyunghyun and Gurevych, Iryna}, booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations}, pages={46--54}, year={2020} } ```

نیازمندی

مقدار	نام
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>=1.0	torch
!=0.11.3,>=0.11.1	tokenizers
>=4.27	tqdm
-	Pillow

زبان مورد نیاز

مقدار	نام
>=3.6.0	Python

نحوه نصب

نصب پکیج whl cody-adapter-transformers-3.0.1:

pip install cody-adapter-transformers-3.0.1.whl

نصب پکیج tar.gz cody-adapter-transformers-3.0.1:

pip install cody-adapter-transformers-3.0.1.tar.gz