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[Time series] Add PatchTSMixer (#26247)
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* patchtsmixer initial commit

* x,y->context_values,target_values, unittest addded

* cleanup code

* minor

* return hidden states

* model tests, partial integration tests

* ettm notebook temporary

* minor

* config mask bug fix, tests updated

* final ETT notebooks

* add selfattn

* init

* added docstrings

* PatchTSMixerForPretraining -> PatchTSMixerForMaskPretraining

* functionality tests added

* add start and input docstrings

* docstring edits

* testcase edits

* minor changes

* docstring error fixed

* ran make fixup

* finalize integration tests and docs

* minor

* cleaned gitignore

* added dataclass decorator, ran black formatter

* ran ruff

* formatting

* add slow decorator

* renamed in_Channel to input_size and default to 1

* shorten dataclass names

* use smaller model for testing

* moved the 3 heads to the modeling file

* use scalers instead of revin

* support forecast_channel_indices

* fix regression scaling

* undo reg. scaling

* removed unneeded classes

* forgot missing

* add more layers

* add copied positional_encoding

* use patchmask from patchtst

* removed dependency on layers directory

* formatting

* set seed

* removed unused imports

* fixed forward signature test

* adding distributional head for PatchTSMixerForecasting

* add generate to forecast

* testcases for generate

* add generate and distributional head for regression

* raise Exception for negative values for neg binominal distribution

* formatting changes

* remove copied from patchtst and add TODO for test passing

* make copies

* doc edits

* minor changes

* format issues

* minor changes

* minor changes

* format docstring

* change some class names to PatchTSMixer + class name

Transpose to PatchTSMixerTranspose
GatedAttention to PatchTSMixerGatedAttention

* change NormLayer to PatchTSMixerNormLayer

* change MLP to PatchTSMixerMLP

* change PatchMixer to PatchMixerBlock, FeatureMixer to FeatureMixerBlock

* change ChannelFeatureMixer to ChannelFeatureMixerBlock

* change PatchMasking to PatchTSMixerMasking

* change Patchify to PatchTSMixerPatchify

* list to `list`

* fix docstrings

* formatting

* change bs to batch_size, edit forecast_masking

* edit random_masking

* change variable name and update docstring in PatchTSMixerMasking

* change variable name and update docstring in InjectScalerStatistics4D

* update forward call in PatchTSMixerTranspose

* change variable name and update docstring in PatchTSMixerNormLayer

* change variable name and update docstring in PatchTSMixerMLP

* change variable name and update docstring in ChannelFeatureMixerBlock

* formatting

* formatting issues

* docstring issue

* fixed observed_mask type in docstrings

* use FloatTensor type

* formatting

* fix rescaling issue in forecasting, fixed integration tests

* add docstring from decorator

* fix docstring

* Update README.md

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/patchtsmixer/configuration_patchtsmixer.py

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/patchtsmixer/modeling_patchtsmixer.py

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/patchtsmixer/configuration_patchtsmixer.py

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/patchtsmixer/modeling_patchtsmixer.py

Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* PatchTSMixerChannelFeatureMixerBlock

* formatting

* ForPretraining

* use num_labels instead of n_classes

* remove commented out code

* docstring fixed

* nn.functional used instead of one letter F

* x_tmp renamed

* one letter variable x removed from forward calls

* one letter variable y removed

* remove commented code

* rename patch_size, in_channels, PatchTSMixerBackbone

* add config to heads

* add config to heads tests

* code reafactoring to use config instead of passing individual params

* Cdocstring fixes part 1

* docstring fixes part 2

* removed logger.debug

* context_values -> past_values

* formatting changes

* pe -> positional_encoding

* removed unused target variable

* self.mode logic fixed

* formatting change

* edit docstring and var name

* change n_targets to num_targets

* rename input_size to num_input_channels

* add head names with prefix PatchTSMixer

* edit docstring in PatchTSMixerForRegression

* fix var name change in testcases

* add PatchTSMixerAttention

* return dict for all exposed classes, test cases added

* format

* move loss function to forward call

* make style

* adding return dict/tuple

* make repo-consistency

* remove flatten mode

* code refactoring

* rename data

* remove PatchTSMixer and keep only PatchTSMixerEncoder

* docstring fixes

* removed unused code

* format

* format

* remove contiguous and formatting changes

* remove model description from config

* replace asserts with ValueError

* remove nn.Sequential from PatchTSMixerNormLayer

* replace if-else with map

* remove all nn.Sequential

* format

* formatting

* fix gradient_checkpointing error after merge, and formatting

* make fix-copies

* remove comments

* reshape

* doesnt support gradient checkpointing

* corect Patchify

* masking updates

* batchnorm copy from

* format checks

* scaler edits

* remove comments

* format changes

* remove self.config

* correct class PatchTSMixerMLP(nn.Module):

* makr fix

* doc updates

* fix-copies

* scaler class correction

* doc edits

* scaler edits

* update readme with links

* injectstatistics add

* fix-copies

* add norm_eps option to LayerNorm

* format changes

* fix copies

* correct make copies

* use parametrize

* fix doc string

* add docs to toctree

* make style

* doc segmenting

* docstring edit

* change forecast to prediction

* edit doc

* doc edits

* remove PatchTSMixerTranspose

* add PatchTSMixerPositionalEncoding and init position_enc

* remove positional_encoding

* edit forecast_masking, remove forecast_mask_ratios

* fix broken code

* var rename target_values -> future_values

* num_features -> d_model

* fix broken code after master merge

* repo consistency

* use postional embedding

* prediction_logits -> prediction_outputs, make fix-copies

* uncommented @slow

* minor changes

* loss first in tuple

* tuple and dict same ordering

* style edits

* minor changes

* dict/tuple consistent enablement

* Update src/transformers/models/patchtsmixer/modeling_patchtsmixer.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update tests/models/patchtsmixer/test_modeling_patchtsmixer.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/patchtsmixer/modeling_patchtsmixer.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix formatting

* formatting

* usage tip

* test on cpu only

* add sample usage

* change PatchTSMixerForClassification to PatchTSMixerForTimeSeriesClassification

* push changes

* fix copies

* std scaling set to default True case

* minor changes

* stylechanges

---------

Co-authored-by: Arindam Jati <arindam.jati@ibm.com>
Co-authored-by: vijaye12 <vijaye12@in.ibm.com>
Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com>
Co-authored-by: nnguyen <nnguyen@us.ibm.com>
Co-authored-by: vijaye12 <vijaykr.e@gmail.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Nam Nguyen <namctin@gmail.com>
Co-authored-by: Wesley Gifford <79663411+wgifford@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
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1 change: 1 addition & 0 deletions README.md
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Expand Up @@ -440,6 +440,7 @@ Current number of checkpoints: ![](https://img.shields.io/endpoint?url=https://h
1. **[OPT](https://huggingface.co/docs/transformers/master/model_doc/opt)** (from Meta AI) released with the paper [OPT: Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) by Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen et al.
1. **[OWL-ViT](https://huggingface.co/docs/transformers/model_doc/owlvit)** (from Google AI) released with the paper [Simple Open-Vocabulary Object Detection with Vision Transformers](https://arxiv.org/abs/2205.06230) by Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, and Neil Houlsby.
1. **[OWLv2](https://huggingface.co/docs/transformers/model_doc/owlv2)** (from Google AI) released with the paper [Scaling Open-Vocabulary Object Detection](https://arxiv.org/abs/2306.09683) by Matthias Minderer, Alexey Gritsenko, Neil Houlsby.
1. **[PatchTSMixer](https://huggingface.co/docs/transformers/main/model_doc/patchtsmixer)** (from IBM Research) released with the paper [TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting](https://arxiv.org/pdf/2306.09364.pdf) by Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam.
1. **[PatchTST](https://huggingface.co/docs/transformers/main/model_doc/patchtst)** (from IBM) released with the paper [A Time Series is Worth 64 Words: Long-term Forecasting with Transformers](https://arxiv.org/abs/2211.14730) by Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, Jayant Kalagnanam.
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. **[PEGASUS-X](https://huggingface.co/docs/transformers/model_doc/pegasus_x)** (from Google) released with the paper [Investigating Efficiently Extending Transformers for Long Input Summarization](https://arxiv.org/abs/2208.04347) by Jason Phang, Yao Zhao, and Peter J. Liu.
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1 change: 1 addition & 0 deletions README_es.md
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Expand Up @@ -415,6 +415,7 @@ Número actual de puntos de control: ![](https://img.shields.io/endpoint?url=htt
1. **[OPT](https://huggingface.co/docs/transformers/master/model_doc/opt)** (from Meta AI) released with the paper [OPT: Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) by Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen et al.
1. **[OWL-ViT](https://huggingface.co/docs/transformers/model_doc/owlvit)** (from Google AI) released with the paper [Simple Open-Vocabulary Object Detection with Vision Transformers](https://arxiv.org/abs/2205.06230) by Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, and Neil Houlsby.
1. **[OWLv2](https://huggingface.co/docs/transformers/model_doc/owlv2)** (from Google AI) released with the paper [Scaling Open-Vocabulary Object Detection](https://arxiv.org/abs/2306.09683) by Matthias Minderer, Alexey Gritsenko, Neil Houlsby.
1. **[PatchTSMixer](https://huggingface.co/docs/transformers/main/model_doc/patchtsmixer)** (from IBM Research) released with the paper [TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting](https://arxiv.org/pdf/2306.09364.pdf) by Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam.
1. **[PatchTST](https://huggingface.co/docs/transformers/main/model_doc/patchtst)** (from IBM) released with the paper [A Time Series is Worth 64 Words: Long-term Forecasting with Transformers](https://arxiv.org/pdf/2211.14730.pdf) by Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, Jayant Kalagnanam.
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. **[PEGASUS-X](https://huggingface.co/docs/transformers/model_doc/pegasus_x)** (from Google) released with the paper [Investigating Efficiently Extending Transformers for Long Input Summarization](https://arxiv.org/abs/2208.04347) by Jason Phang, Yao Zhao, and Peter J. Liu.
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1 change: 1 addition & 0 deletions README_hd.md
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Expand Up @@ -389,6 +389,7 @@ conda install -c huggingface transformers
1. **[OPT](https://huggingface.co/docs/transformers/master/model_doc/opt)** (from Meta AI) released with the paper [OPT: Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) by Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen et al.
1. **[OWL-ViT](https://huggingface.co/docs/transformers/model_doc/owlvit)** (Google AI से) साथ में कागज [विज़न ट्रांसफॉर्मर्स के साथ सिंपल ओपन-वोकैबुलरी ऑब्जेक्ट डिटेक्शन](https:/ /arxiv.org/abs/2205.06230) मैथियास मिंडरर, एलेक्सी ग्रिट्सेंको, ऑस्टिन स्टोन, मैक्सिम न्यूमैन, डिर्क वीसेनबोर्न, एलेक्सी डोसोवित्स्की, अरविंद महेंद्रन, अनुराग अर्नब, मुस्तफा देहघानी, ज़ुओरन शेन, जिओ वांग, ज़ियाओहुआ झाई, थॉमस किफ़, और नील हॉल्सबी द्वारा पोस्ट किया गया।
1. **[OWLv2](https://huggingface.co/docs/transformers/model_doc/owlv2)** (Google AI से) Matthias Minderer, Alexey Gritsenko, Neil Houlsby. द्वाराअनुसंधान पत्र [Scaling Open-Vocabulary Object Detection](https://arxiv.org/abs/2306.09683) के साथ जारी किया गया
1. **[PatchTSMixer](https://huggingface.co/docs/transformers/main/model_doc/patchtsmixer)** ( IBM Research से) Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam. द्वाराअनुसंधान पत्र [TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting](https://arxiv.org/pdf/2306.09364.pdf) के साथ जारी किया गया
1. **[PatchTST](https://huggingface.co/docs/transformers/main/model_doc/patchtst)** (IBM से) Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, Jayant Kalagnanam. द्वाराअनुसंधान पत्र [A Time Series is Worth 64 Words: Long-term Forecasting with Transformers](https://arxiv.org/pdf/2211.14730.pdf) के साथ जारी किया गया
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. **[PEGASUS-X](https://huggingface.co/docs/transformers/model_doc/pegasus_x)** (Google की ओर से) साथ में दिया गया पेपर [लंबे इनपुट सारांश के लिए ट्रांसफ़ॉर्मरों को बेहतर तरीके से एक्सटेंड करना](https://arxiv .org/abs/2208.04347) जेसन फांग, याओ झाओ, पीटर जे लियू द्वारा।
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1 change: 1 addition & 0 deletions README_ja.md
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Expand Up @@ -449,6 +449,7 @@ Flax、PyTorch、TensorFlowをcondaでインストールする方法は、それ
1. **[OPT](https://huggingface.co/docs/transformers/master/model_doc/opt)** (Meta AI から) Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen et al から公開された研究論文: [OPT: Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068)
1. **[OWL-ViT](https://huggingface.co/docs/transformers/model_doc/owlvit)** (Google AI から) Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, and Neil Houlsby から公開された研究論文: [Simple Open-Vocabulary Object Detection with Vision Transformers](https://arxiv.org/abs/2205.06230)
1. **[OWLv2](https://huggingface.co/docs/transformers/model_doc/owlv2)** (Google AI から) Matthias Minderer, Alexey Gritsenko, Neil Houlsby. から公開された研究論文 [Scaling Open-Vocabulary Object Detection](https://arxiv.org/abs/2306.09683)
1. **[PatchTSMixer](https://huggingface.co/docs/transformers/main/model_doc/patchtsmixer)** ( IBM Research から) Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam. から公開された研究論文 [TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting](https://arxiv.org/pdf/2306.09364.pdf)
1. **[PatchTST](https://huggingface.co/docs/transformers/main/model_doc/patchtst)** (IBM から) Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, Jayant Kalagnanam. から公開された研究論文 [A Time Series is Worth 64 Words: Long-term Forecasting with Transformers](https://arxiv.org/pdf/2211.14730.pdf)
1. **[Pegasus](https://huggingface.co/docs/transformers/model_doc/pegasus)** (Google から) Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu から公開された研究論文: [PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization](https://arxiv.org/abs/1912.08777)
1. **[PEGASUS-X](https://huggingface.co/docs/transformers/model_doc/pegasus_x)** (Google から) Jason Phang, Yao Zhao, and Peter J. Liu から公開された研究論文: [Investigating Efficiently Extending Transformers for Long Input Summarization](https://arxiv.org/abs/2208.04347)
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1 change: 1 addition & 0 deletions README_ko.md
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Expand Up @@ -364,6 +364,7 @@ Flax, PyTorch, TensorFlow 설치 페이지에서 이들을 conda로 설치하는
1. **[OPT](https://huggingface.co/docs/transformers/master/model_doc/opt)** (Meta AI 에서) Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen et al 의 [OPT: Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) 논문과 함께 발표했습니다.
1. **[OWL-ViT](https://huggingface.co/docs/transformers/model_doc/owlvit)** (Google AI 에서) Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, and Neil Houlsby 의 [Simple Open-Vocabulary Object Detection with Vision Transformers](https://arxiv.org/abs/2205.06230) 논문과 함께 발표했습니다.
1. **[OWLv2](https://huggingface.co/docs/transformers/model_doc/owlv2)** (Google AI 에서 제공)은 Matthias Minderer, Alexey Gritsenko, Neil Houlsby.의 [Scaling Open-Vocabulary Object Detection](https://arxiv.org/abs/2306.09683)논문과 함께 발표했습니다.
1. **[PatchTSMixer](https://huggingface.co/docs/transformers/main/model_doc/patchtsmixer)** ( IBM Research 에서 제공)은 Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam.의 [TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting](https://arxiv.org/pdf/2306.09364.pdf)논문과 함께 발표했습니다.
1. **[PatchTST](https://huggingface.co/docs/transformers/main/model_doc/patchtst)** (IBM 에서 제공)은 Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, Jayant Kalagnanam.의 [A Time Series is Worth 64 Words: Long-term Forecasting with Transformers](https://arxiv.org/pdf/2211.14730.pdf)논문과 함께 발표했습니다.
1. **[Pegasus](https://huggingface.co/docs/transformers/model_doc/pegasus)** (Google 에서) Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu 의 [PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization](https://arxiv.org/abs/1912.08777) 논문과 함께 발표했습니다.
1. **[PEGASUS-X](https://huggingface.co/docs/transformers/model_doc/pegasus_x)** (Google 에서) Jason Phang, Yao Zhao, Peter J. Liu 의 [Investigating Efficiently Extending Transformers for Long Input Summarization](https://arxiv.org/abs/2208.04347) 논문과 함께 발표했습니다.
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1 change: 1 addition & 0 deletions README_zh-hans.md
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Expand Up @@ -388,6 +388,7 @@ conda install -c huggingface transformers
1. **[OPT](https://huggingface.co/docs/transformers/master/model_doc/opt)** (来自 Meta AI) 伴随论文 [OPT: Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) 由 Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen et al 发布。
1. **[OWL-ViT](https://huggingface.co/docs/transformers/model_doc/owlvit)** (来自 Google AI) 伴随论文 [Simple Open-Vocabulary Object Detection with Vision Transformers](https://arxiv.org/abs/2205.06230) 由 Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, and Neil Houlsby 发布。
1. **[OWLv2](https://huggingface.co/docs/transformers/model_doc/owlv2)** (来自 Google AI) 伴随论文 [Scaling Open-Vocabulary Object Detection](https://arxiv.org/abs/2306.09683) 由 Matthias Minderer, Alexey Gritsenko, Neil Houlsby 发布。
1. **[PatchTSMixer](https://huggingface.co/docs/transformers/main/model_doc/patchtsmixer)** (来自 IBM Research) 伴随论文 [TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting](https://arxiv.org/pdf/2306.09364.pdf) 由 Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam 发布。
1. **[PatchTST](https://huggingface.co/docs/transformers/main/model_doc/patchtst)** (来自 IBM) 伴随论文 [A Time Series is Worth 64 Words: Long-term Forecasting with Transformers](https://arxiv.org/pdf/2211.14730.pdf) 由 Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, Jayant Kalagnanam 发布。
1. **[Pegasus](https://huggingface.co/docs/transformers/model_doc/pegasus)** (来自 Google) 伴随论文 [PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization](https://arxiv.org/abs/1912.08777) 由 Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu 发布。
1. **[PEGASUS-X](https://huggingface.co/docs/transformers/model_doc/pegasus_x)** (来自 Google) 伴随论文 [Investigating Efficiently Extending Transformers for Long Input Summarization](https://arxiv.org/abs/2208.04347) 由 Jason Phang, Yao Zhao, Peter J. Liu 发布。
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1 change: 1 addition & 0 deletions README_zh-hant.md
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Expand Up @@ -400,6 +400,7 @@ conda install -c huggingface transformers
1. **[OPT](https://huggingface.co/docs/transformers/master/model_doc/opt)** (from Meta AI) released with the paper [OPT: Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) by Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen et al.
1. **[OWL-ViT](https://huggingface.co/docs/transformers/model_doc/owlvit)** (from Google AI) released with the paper [Simple Open-Vocabulary Object Detection with Vision Transformers](https://arxiv.org/abs/2205.06230) by Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, and Neil Houlsby.
1. **[OWLv2](https://huggingface.co/docs/transformers/model_doc/owlv2)** (from Google AI) released with the paper [Scaling Open-Vocabulary Object Detection](https://arxiv.org/abs/2306.09683) by Matthias Minderer, Alexey Gritsenko, Neil Houlsby.
1. **[PatchTSMixer](https://huggingface.co/docs/transformers/main/model_doc/patchtsmixer)** (from IBM Research) released with the paper [TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting](https://arxiv.org/pdf/2306.09364.pdf) by Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam.
1. **[PatchTST](https://huggingface.co/docs/transformers/main/model_doc/patchtst)** (from IBM) released with the paper [A Time Series is Worth 64 Words: Long-term Forecasting with Transformers](https://arxiv.org/pdf/2211.14730.pdf) by Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, Jayant Kalagnanam.
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. **[PEGASUS-X](https://huggingface.co/docs/transformers/model_doc/pegasus_x)** (from Google) released with the paper [Investigating Efficiently Extending Transformers for Long Input Summarization](https://arxiv.org/abs/2208.04347) by Jason Phang, Yao Zhao, Peter J. Liu.
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2 changes: 2 additions & 0 deletions docs/source/en/_toctree.yml
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title: Autoformer
- local: model_doc/informer
title: Informer
- local: model_doc/patchtsmixer
title: PatchTSMixer
- local: model_doc/patchtst
title: PatchTST
- local: model_doc/time_series_transformer
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1 change: 1 addition & 0 deletions docs/source/en/index.md
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| [OPT](model_doc/opt) ||||
| [OWL-ViT](model_doc/owlvit) ||||
| [OWLv2](model_doc/owlv2) ||||
| [PatchTSMixer](model_doc/patchtsmixer) ||||
| [PatchTST](model_doc/patchtst) ||||
| [Pegasus](model_doc/pegasus) ||||
| [PEGASUS-X](model_doc/pegasus_x) ||||
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