Add DeiT API usage documentation

[sachinprasadhs]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @sachinprasadhs, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request focuses on enhancing the project's documentation by integrating the DeiT (Data-efficient Image Transformers) API components into the automated documentation generation system. The changes primarily involve updating the documentation configuration to ensure that key DeiT models, layers, and their associated methods and properties are properly documented and accessible. This will improve the discoverability and usability of the DeiT API for developers.

Highlights

• DeiTImageConverter Documentation: This pull request introduces the necessary configuration to automatically generate API documentation for the DeiTImageConverter layer, including its from_preset method.
• DeiTBackbone Model Documentation: Configuration has been added to generate documentation for the DeiTBackbone model, covering its main class and the from_preset method.
• DeiTImageClassifier Model Documentation: The changes include setting up documentation generation for the DeiTImageClassifier model, its from_preset method, and its backbone and preprocessor properties.
• DeiTImageClassifierPreprocessor Documentation: Documentation will now be generated for the DeiTImageClassifierPreprocessor layer, including its from_preset method and the image_converter property.

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[gemini-code-assist]

Code Review

This pull request adds the necessary configuration to scripts/hub_master.py to generate API documentation for the DeiT (Data-efficient image Transformers) models. The changes are well-structured and consistent with existing model documentation entries in the file. The new entry for DeiT is placed in correct alphabetical order and includes documentation for DeiTImageConverter, DeiTBackbone, DeiTImageClassifier, and DeiTImageClassifierPreprocessor. The code looks good and I have no suggestions for improvement.