Updated the model card for wav2vec2-phoneme
Author: AshAnand34
Pull request: yes

# What does this PR do?

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This pull request updates the documentation for the `Wav2Vec2Phoneme` model to improve readability, provide more examples, and clarify its usage. The changes include a revamped introduction, added usage examples, and detailed explanations of the model's features and capabilities.

### Documentation Enhancements:

* **Introduction and Overview**: Replaced the plain text introduction with a visually appealing layout that includes badges for supported frameworks (PyTorch, TensorFlow, Flax) and a clear explanation of the `Wav2Vec2Phoneme` model's purpose and capabilities. Added links to relevant papers and model checkpoints.

* **Usage Examples**: Introduced two detailed code examples for phoneme recognition using the `Pipeline` and `AutoModel` classes. These examples demonstrate how to load the model, process audio data, and decode phonemes.

* **Quantization Support**: Added a section on quantization, including an example of using `bitsandbytes` to load the model with 8-bit precision, reducing memory usage.

### Detailed Feature Descriptions:

* **Model Features**: Expanded on the model's architecture, cross-lingual capabilities, and performance. Explained its ability to map phonemes across languages and its use of connectionist temporal classification (CTC) for training. (Ff214

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#36979


## Before submitting
- [x] 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

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Models:

- text models: @ArthurZucker
- vision models: @amyeroberts, @qubvel
- speech models: @eustlb
- graph models: @clefourrier

Library:

- flax: @gante and @Rocketknight1
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Rocketknight1
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @zach-huggingface, @SunMarc and @qgallouedec
- chat templates: @Rocketknight1

Integrations:

- deepspeed: HF Trainer/Accelerate: @SunMarc @zach-huggingface
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc @MekkCyber

Documentation: @stevhliu

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @Rocketknight1
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1

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