[Frontend] [Core] perf: Automatically detect vLLM-tensorized model, update tensorizer to version 2.9.0

[sangstar]

Automatically detect vLLM-tensorized model, update tensorizer to version 2.9.0

This PR accomplishes several things:

• Updates docstrings to account for tensorizer refactor in [Core] Refactor model loading code #4097 in the tensorize_vllm_examples.py example script, and slight corrections to the docstrings of the new, refactored functions.
• Allows models to be automatically inferred as a vLLM-tensorized model. Accomplishes this by placing a meta-tensor "footprint" in the serialized model, and removing it at runtime. vllm_tensorized as an arg has been removed.
• Updates tensorizer to the full release of 2.9.0.

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[sangstar]

@Yard1 @ywang96

Some QoL improvements for tensorizer and some corrected docstrings (as per the great refactor from @Yard1), and an update for tensorizer as version 1.9.0 is officially released. No longer need to specify if a model is vLLM-tensorized beforehand, as I've implemented a way for this to be inferred implicitly by registering a meta tensor into the model during serialization with a vllm-tensorized-marker and removing it during deserialization.

[sangstar]

Further made some improvements with documentation. Important fixes explaining how to use tensorizer with the refactored changes (as the example script predates the refactor) so hoping to get eyes on this! Cheers :D
@ywang96 @Yard1

[ywang96]

Will take a look once I have some bandwidth - thanks for the continuous contribution to vLLM!

[ywang96]

Thank you @sangstar for the continuous contribution! I left some questions.

[sangstar]

@ywang96 Resolved comments! Let me know if anything else is needed.

[sangstar]

@ywang96 Resolved comments!

[ywang96]

🚀 LGTM!

[sangstar]

@ywang96 Checks passed and ready to merge! 😄