[AshAnand34]

What does this PR do?

This pull request significantly enhances the documentation for the Wav2Vec2-Conformer model by improving its structure, adding usage examples, and providing detailed explanations of its architecture and features. It also introduces quantization support and updates the API reference for better clarity.

Documentation Enhancements:

• Reorganized the Wav2Vec2-Conformer documentation to include a more structured overview, detailed usage examples, and tips for applying the model to different tasks. Examples include automatic speech recognition and audio classification using both the Pipeline and AutoModel classes.
• Added a section on quantization, demonstrating how to use bitsandbytes for 8-bit model quantization to reduce memory usage.

Architectural and Feature Details:

• Expanded the explanation of the Wav2Vec2-Conformer architecture, highlighting its use of Conformer blocks for improved speech recognition performance and its compatibility with Wav2Vec2 workflows.
• Included notes on position embedding types, tokenizer compatibility, and performance improvements, along with links to official results and related resources.

API Reference Updates:

• Updated the API reference with detailed sections for Wav2Vec2ConformerConfig, Wav2Vec2ConformerModel, and other related classes, ensuring a clear

#36979

Before submitting

• This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).

Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

@stevhliu

[ArthurZucker]

Thanks for the PR, and sorry it didn't make it in! This branch is based on v4, and v5 is very different, so rather than rebasing we'd love to invite you to open a new PR against main using our latest tools and good practices:

• Transformers tenets
• mlinter and the modeling rules it enforces (make typing)
• Modular transformers
• Contributing guide

Closing this one in the meantime, thanks again!