highlights QAT in guide title

[JyotinderSingh]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @JyotinderSingh, 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 enhances the accuracy and clarity of the documentation for a Keras example by explicitly stating 'Quantization Aware Training' in its title and description. The changes ensure that users immediately understand the specific methodology employed in the Float8 Transformer model guide, improving the overall user experience and reducing potential ambiguity.

Highlights

• Documentation Clarity: Updated the titles and descriptions of the 'Float8 training and inference with a simple Transformer model' guide across its Python, Jupyter Notebook, and Markdown versions to explicitly include 'Quantization Aware Training' (QAT). This clarifies the specific quantization approach demonstrated in the example.
• Metadata Update: Synchronized the title of the Float8 Transformer guide within the scripts/examples_master.py file, which manages example metadata, to reflect the new, more precise QAT-inclusive title.

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[gemini-code-assist]

Code Review

This pull request updates the titles and descriptions across multiple files to more accurately reflect that the example uses Quantization-Aware Training (QAT). The changes are consistent and improve clarity. I've suggested a minor stylistic improvement to hyphenate 'Quantization-Aware' in the titles for better readability and grammatical correctness.