feat: update knowledge distillation tutorial for using vllm with Qwen model

[RexBearIU]

Description

This pull request significantly updates and modernizes the knowledge distillation tutorial for MaxText, aligning it with current best practices and tooling. The guide now uses Qwen3-32B as the teacher model (via vLLM) and Llama-3.1-8B as the student, streamlines the setup with Hyperdisk storage, and provides new scripts and commands for dataset generation and fine-tuning. The instructions have been clarified, unnecessary conversion steps removed for the teacher, and the fine-tuning process updated for the latest MaxText and vLLM workflows.

Tests

Manually triggered the distillation pipeline and monitored the execution flow step-by-step. Confirmed that the training loop finished and resources were released.

Checklist

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• I have performed a self-review of my code. For an optional AI review, add the gemini-review label.
• I have necessary comments in my code, particularly in hard-to-understand areas.
• I have run end-to-end tests tests and provided workload links above if applicable.
• I have made or will make corresponding changes to the doc if needed, including adding new documentation pages to the relevant Table of Contents (toctree directive) as explained in our documentation.