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+*This model was published in HF papers on 2020-10-11 and contributed to Hugging Face Transformers on 2022-05-17.*
+
+# Wav2Vec2-Conformer
+
+
+## Overview
+
+The Wav2Vec2-Conformer was added to an updated version of [fairseq S2T: Fast Speech-to-Text Modeling with fairseq](https://huggingface.co/papers/2010.05171) by Changhan Wang, Yun Tang, Xutai Ma, Anne Wu, Sravya Popuri, Dmytro Okhonko, Juan Pino.
+
+The official results of the model can be found in Table 3 and Table 4 of the paper.
+
+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).
+
+This model was contributed by [patrickvonplaten](https://huggingface.co/patrickvonplaten).
+The original code can be found [here](https://github.com/pytorch/fairseq/tree/main/examples/wav2vec).
+
+Note: Meta (FAIR) released a new version of [Wav2Vec2-BERT 2.0](https://huggingface.co/docs/transformers/en/model_doc/wav2vec2-bert) - it's pretrained on 4.5M hours of audio. We especially recommend using it for fine-tuning tasks, e.g. as per [this guide](https://huggingface.co/blog/fine-tune-w2v2-bert).
+
+## Usage tips
+
+- Wav2Vec2-Conformer follows the same architecture as Wav2Vec2, but replaces the *Attention*-block with a *Conformer*-block
+  as introduced in [Conformer: Convolution-augmented Transformer for Speech Recognition](https://huggingface.co/papers/2005.08100).
+- For the same number of layers, Wav2Vec2-Conformer requires more parameters than Wav2Vec2, but also yields
+an improved word error rate.
+- Wav2Vec2-Conformer uses the same tokenizer and feature extractor as Wav2Vec2.
+- Wav2Vec2-Conformer can use either no relative position embeddings, Transformer-XL-like position embeddings, or
+  rotary position embeddings by setting the correct `config.position_embeddings_type`.
+
+## Resources
+
+- [Audio classification task guide](../tasks/audio_classification)
+- [Automatic speech recognition task guide](../tasks/asr)
+
+## Wav2Vec2ConformerConfig
+
+[[autodoc]] Wav2Vec2ConformerConfig
+
+## Wav2Vec2Conformer specific outputs
+
+[[autodoc]] models.wav2vec2_conformer.modeling_wav2vec2_conformer.Wav2Vec2ConformerForPreTrainingOutput
+
+## Wav2Vec2ConformerModel
+
+[[autodoc]] Wav2Vec2ConformerModel
+    - forward
+
+## Wav2Vec2ConformerForCTC
+
+[[autodoc]] Wav2Vec2ConformerForCTC
+    - forward
+
+## Wav2Vec2ConformerForSequenceClassification
+
+[[autodoc]] Wav2Vec2ConformerForSequenceClassification
+    - forward
+
+## Wav2Vec2ConformerForAudioFrameClassification
+
+[[autodoc]] Wav2Vec2ConformerForAudioFrameClassification
+    - forward
+
+## Wav2Vec2ConformerForXVector
+
+[[autodoc]] Wav2Vec2ConformerForXVector
+    - forward
+
+## Wav2Vec2ConformerForPreTraining
+
+[[autodoc]] Wav2Vec2ConformerForPreTraining
+    - forward