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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the License. You may obtain a copy of the License at
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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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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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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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# Wav2Vec2-Conformer
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## Overview
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The Wav2Vec2-Conformer was added to an updated version of [fairseq S2T: Fast Speech-to-Text Modeling with fairseq](https://arxiv.org/abs/2010.05171) by Changhan Wang, Yun Tang, Xutai Ma, Anne Wu, Sravya Popuri, Dmytro Okhonko, Juan Pino.
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The official results of the model can be found in Table 3 and Table 4 of the paper.
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The Wav2Vec2-Conformer weights were released by the Meta AI team within the [Fairseq library](https://github.com/pytorch/fairseq/blob/main/examples/wav2vec/README.md#pre-trained-models).
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Tips:
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- Wav2Vec2-Conformer follows the same architecture as Wav2Vec2, but replaces the *Attention*-block with a *Conformer*-block
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as introduced in [Conformer: Convolution-augmented Transformer for Speech Recognition](https://arxiv.org/abs/2005.08100).
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- For the same number of layers, Wav2Vec2-Conformer requires more parameters than Wav2Vec2, but also yields
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an improved word error rate.
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- Wav2Vec2-Conformer uses the same tokenizer and feature extractor as Wav2Vec2.
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- Wav2Vec2-Conformer can use either no relative position embeddings, Transformer-XL-like position embeddings, or
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rotary position embeddings by setting the correct `config.position_embeddings_type`.
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This model was contributed by [patrickvonplaten](https://huggingface.co/patrickvonplaten).
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The original code can be found [here](https://github.com/pytorch/fairseq/tree/main/examples/wav2vec).
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## Documentation resources
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- [Audio classification task guide](../tasks/audio_classification)
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- [Automatic speech recognition task guide](../tasks/asr)
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## Wav2Vec2ConformerConfig
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[[autodoc]] Wav2Vec2ConformerConfig
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## Wav2Vec2Conformer specific outputs
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[[autodoc]] models.wav2vec2_conformer.modeling_wav2vec2_conformer.Wav2Vec2ConformerForPreTrainingOutput
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## Wav2Vec2ConformerModel
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[[autodoc]] Wav2Vec2ConformerModel
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- forward
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## Wav2Vec2ConformerForCTC
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[[autodoc]] Wav2Vec2ConformerForCTC
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- forward
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## Wav2Vec2ConformerForSequenceClassification
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[[autodoc]] Wav2Vec2ConformerForSequenceClassification
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- forward
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## Wav2Vec2ConformerForAudioFrameClassification
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[[autodoc]] Wav2Vec2ConformerForAudioFrameClassification
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- forward
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## Wav2Vec2ConformerForXVector
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[[autodoc]] Wav2Vec2ConformerForXVector
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- forward
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## Wav2Vec2ConformerForPreTraining
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[[autodoc]] Wav2Vec2ConformerForPreTraining
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- forward
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