Add PoolFormer (#15531)

* Added all files, PoolFormerFeatureExtractor still failing tests

* Fixed PoolFormerFeatureExtractor not being able to import

* Completed Poolformer doc

* Applied Suggested fixes

* Fixed errors in modeling_auto.py

* Fix feature extractor, convert docs to Markdown, styling of code

* Remove PoolFormer from check_repo and fix integration test

* Remove Poolformer from check_repo

* Fixed configuration_poolformer.py docs and removed inference.py from poolformer

* Ran with black v22

* Added PoolFormer to _toctree.yml

* Updated poolformer doc

* Applied suggested fixes and added on README.md

* Did make fixup and make fix-copies, tests should pass now

* Changed PoolFormer weights conversion script name and fixed README

* Applied fixes in test_modeling_poolformer.py and modeling_poolformer.py

* Added PoolFormerFeatureExtractor to AutoFeatureExtractor API

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>
This commit is contained in:
Tanay Mehta
2022-02-17 17:46:37 +05:30
committed by GitHub
parent 0e91f885c3
commit f84e0dbd2a
21 changed files with 1719 additions and 0 deletions

View File

@@ -269,6 +269,7 @@ Flax, PyTorch, TensorFlow 설치 페이지에서 이들을 conda로 설치하는
1. **[Pegasus](https://huggingface.co/docs/transformers/model_doc/pegasus)** (from Google) released with the paper [PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization](https://arxiv.org/abs/1912.08777) by Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu.
1. **[Perceiver IO](https://huggingface.co/docs/transformers/model_doc/perceiver)** (from Deepmind) released with the paper [Perceiver IO: A General Architecture for Structured Inputs & Outputs](https://arxiv.org/abs/2107.14795) by Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira.
1. **[PhoBERT](https://huggingface.co/docs/transformers/model_doc/phobert)** (from VinAI Research) released with the paper [PhoBERT: Pre-trained language models for Vietnamese](https://www.aclweb.org/anthology/2020.findings-emnlp.92/) by Dat Quoc Nguyen and Anh Tuan Nguyen.
1. **[PoolFormer](https://huggingface.co/docs/transformers/master/model_doc/poolformer)** (from Sea AI Labs) released with the paper [MetaFormer is Actually What You Need for Vision](https://arxiv.org/abs/2111.11418) by Yu, Weihao and Luo, Mi and Zhou, Pan and Si, Chenyang and Zhou, Yichen and Wang, Xinchao and Feng, Jiashi and Yan, Shuicheng.
1. **[ProphetNet](https://huggingface.co/docs/transformers/model_doc/prophetnet)** (from Microsoft Research) released with the paper [ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training](https://arxiv.org/abs/2001.04063) by Yu Yan, Weizhen Qi, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang and Ming Zhou.
1. **[QDQBert](https://huggingface.co/docs/transformers/model_doc/qdqbert)** (from NVIDIA) released with the paper [Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation](https://arxiv.org/abs/2004.09602) by Hao Wu, Patrick Judd, Xiaojie Zhang, Mikhail Isaev and Paulius Micikevicius.
1. **[REALM](https://huggingface.co/transformers/model_doc/realm.html)** (from Google Research) released with the paper [REALM: Retrieval-Augmented Language Model Pre-Training](https://arxiv.org/abs/2002.08909) by Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat and Ming-Wei Chang.