Improve vLLM examples regarding vllm_engine_kwargs use

[3manifold]

PR type

• Document Updates

PR information

Add an example of an advanced usecase of --vllm_engine_kwargs use since there was no similar example in the past. It applies to vllm >= 0.13.0.
List of input vLLM args can be found here vllm-project/vllm#26315 . It relates to #7132 .

[gemini-code-assist]

Summary of Changes

Hello @3manifold, 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 existing vLLM examples by introducing a practical demonstration of how to utilize the --vllm_engine_kwargs argument for advanced engine configurations. The update specifically illustrates how to enable Flash Attention, which can lead to performance improvements in compatible vLLM environments. This addition aims to provide clearer guidance for users looking to optimize their vLLM deployments.

Highlights

• Documentation Update: This pull request primarily focuses on updating documentation by adding a new example.
• Advanced vLLM Engine Configuration: An advanced use case for the --vllm_engine_kwargs parameter has been added to demonstrate how to configure the vLLM engine, specifically enabling Flash Attention.
• vLLM Version Compatibility: The added example is applicable for vLLM versions 0.13.0 and above.
• Issue Resolution: This change addresses the issue reported in vLLM 0.13.0 causes error due to deprecated VLLM_ATTENTION_BACKEND environment variable #7132.

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[gemini-code-assist]

Code Review

This pull request adds a valuable example demonstrating the use of --vllm_engine_kwargs to configure the attention backend in vLLM. The change is correct and enhances the provided examples. I've added one suggestion to include a comment about the required vLLM version to make the example even more user-friendly.

[3manifold]

vllm | >=0.5.1 | 0.11.0/0.13.0 | Inference/Deployment

Given that the current README.md suggests vllm = 0.13.0, the example in this PR can be quite helpful.