Migrate doc files to Markdown. (#24376)
* Rename index.mdx to index.md * With saved modifs * Address review comment * Treat all files * .mdx -> .md * Remove special char * Update utils/tests_fetcher.py Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr> --------- Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
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<!--Copyright 2022 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
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# RoBERTa-PreLayerNorm
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## Overview
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The RoBERTa-PreLayerNorm model was proposed in [fairseq: A Fast, Extensible Toolkit for Sequence Modeling](https://arxiv.org/abs/1904.01038) by Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, Michael Auli.
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It is identical to using the `--encoder-normalize-before` flag in [fairseq](https://fairseq.readthedocs.io/).
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The abstract from the paper is the following:
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*fairseq is an open-source sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling, and other text generation tasks. The toolkit is based on PyTorch and supports distributed training across multiple GPUs and machines. We also support fast mixed-precision training and inference on modern GPUs.*
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Tips:
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- The implementation is the same as [Roberta](roberta) except instead of using _Add and Norm_ it does _Norm and Add_. _Add_ and _Norm_ refers to the Addition and LayerNormalization as described in [Attention Is All You Need](https://arxiv.org/abs/1706.03762).
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- This is identical to using the `--encoder-normalize-before` flag in [fairseq](https://fairseq.readthedocs.io/).
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This model was contributed by [andreasmaden](https://huggingface.co/andreasmaden).
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The original code can be found [here](https://github.com/princeton-nlp/DinkyTrain).
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## Documentation resources
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- [Text classification task guide](../tasks/sequence_classification)
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- [Token classification task guide](../tasks/token_classification)
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- [Question answering task guide](../tasks/question_answering)
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- [Causal language modeling task guide](../tasks/language_modeling)
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- [Masked language modeling task guide](../tasks/masked_language_modeling)
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- [Multiple choice task guide](../tasks/multiple_choice)
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## RobertaPreLayerNormConfig
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[[autodoc]] RobertaPreLayerNormConfig
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## RobertaPreLayerNormModel
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[[autodoc]] RobertaPreLayerNormModel
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- forward
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## RobertaPreLayerNormForCausalLM
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[[autodoc]] RobertaPreLayerNormForCausalLM
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- forward
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## RobertaPreLayerNormForMaskedLM
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[[autodoc]] RobertaPreLayerNormForMaskedLM
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- forward
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## RobertaPreLayerNormForSequenceClassification
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[[autodoc]] RobertaPreLayerNormForSequenceClassification
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- forward
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## RobertaPreLayerNormForMultipleChoice
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[[autodoc]] RobertaPreLayerNormForMultipleChoice
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- forward
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## RobertaPreLayerNormForTokenClassification
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[[autodoc]] RobertaPreLayerNormForTokenClassification
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- forward
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## RobertaPreLayerNormForQuestionAnswering
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[[autodoc]] RobertaPreLayerNormForQuestionAnswering
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- forward
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## TFRobertaPreLayerNormModel
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[[autodoc]] TFRobertaPreLayerNormModel
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- call
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## TFRobertaPreLayerNormForCausalLM
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[[autodoc]] TFRobertaPreLayerNormForCausalLM
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- call
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## TFRobertaPreLayerNormForMaskedLM
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[[autodoc]] TFRobertaPreLayerNormForMaskedLM
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- call
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## TFRobertaPreLayerNormForSequenceClassification
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[[autodoc]] TFRobertaPreLayerNormForSequenceClassification
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- call
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## TFRobertaPreLayerNormForMultipleChoice
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[[autodoc]] TFRobertaPreLayerNormForMultipleChoice
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- call
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## TFRobertaPreLayerNormForTokenClassification
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[[autodoc]] TFRobertaPreLayerNormForTokenClassification
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- call
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## TFRobertaPreLayerNormForQuestionAnswering
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[[autodoc]] TFRobertaPreLayerNormForQuestionAnswering
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- call
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## FlaxRobertaPreLayerNormModel
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[[autodoc]] FlaxRobertaPreLayerNormModel
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- __call__
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## FlaxRobertaPreLayerNormForCausalLM
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[[autodoc]] FlaxRobertaPreLayerNormForCausalLM
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- __call__
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## FlaxRobertaPreLayerNormForMaskedLM
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[[autodoc]] FlaxRobertaPreLayerNormForMaskedLM
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- __call__
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## FlaxRobertaPreLayerNormForSequenceClassification
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[[autodoc]] FlaxRobertaPreLayerNormForSequenceClassification
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- __call__
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## FlaxRobertaPreLayerNormForMultipleChoice
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[[autodoc]] FlaxRobertaPreLayerNormForMultipleChoice
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- __call__
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## FlaxRobertaPreLayerNormForTokenClassification
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[[autodoc]] FlaxRobertaPreLayerNormForTokenClassification
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- __call__
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## FlaxRobertaPreLayerNormForQuestionAnswering
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[[autodoc]] FlaxRobertaPreLayerNormForQuestionAnswering
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- __call__
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