Refine AutoRound Guide

[yiliu30]

https://github.com/yiliu30/llm-compressor-fork/tree/refine-ar-doc/examples/autoround

[github-actions]

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[gemini-code-assist]

Summary of Changes

Hello @yiliu30, 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 refines the documentation for the AutoRound quantization examples by reorganizing content to provide a clearer separation between high-level conceptual overviews and detailed implementation guides. It also enhances the AutoRound modifier by introducing a configurable learning rate, offering users greater flexibility in optimizing the quantization process.

Highlights

• Documentation Restructuring: The primary autoround README has been refactored to focus on high-level information, including when to use AutoRound, its key parameters, and available quantization recipes. Detailed quickstart and code walkthrough sections have been moved.
• Detailed Example Documentation: A new README.md file has been introduced under examples/autoround/quantization_w4a16/ to house the comprehensive quickstart guide and step-by-step code walkthrough for AutoRound's W4A16 quantization scheme.
• Example File Relocation: The llama3_example.py script has been moved into the newly created quantization_w4a16/ subdirectory, aligning with the updated documentation structure.
• Learning Rate Parameter: The AutoRoundModifier now includes an optional lr (learning rate) parameter, providing more granular control over the quantization tuning process.

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[gemini-code-assist]

Code Review

This pull request refactors the AutoRound documentation by splitting it into a high-level overview and a detailed, example-driven walkthrough. It also introduces a new lr (learning rate) parameter to the AutoRoundModifier. The documentation changes significantly improve clarity and structure. I've pointed out a couple of minor issues in the main README.md file related to a redundant parameter list and incorrect markdown syntax for a link. Overall, this is a great improvement to the documentation.

[yiliu30]

/gemini review

[gemini-code-assist]

Code Review

This pull request refines the documentation for AutoRound by restructuring the main README and moving the detailed walkthrough to a separate file. It also introduces a new lr parameter for the AutoRoundModifier. The documentation changes are clear and improve the structure. I've found a small typo and some formatting suggestions in the markdown files to enhance readability.

[gemini-code-assist]

There are a few extra blank lines here. To improve readability, it's good practice to have only one blank line between paragraphs or sections. Similar extra blank lines can be found at lines 39, 57-58, and 66-67.

[gemini-code-assist]

There seems to be a typo in the example quantization scheme W816. Based on the other examples like W4A16 and the wNa16 format, it should likely be W8A16 to represent 8-bit weights and 16-bit activations.

Suggested change

	- `scheme`: Quantization scheme (e.g., `W4A16`, `W816`, more schemes will be supported soon)
	- `scheme`: Quantization scheme (e.g., `W4A16`, `W8A16`, more schemes will be supported soon)

[gemini-code-assist]

There is a trailing whitespace at the end of this line. It should be removed.

Suggested change

	Load the model using `AutoModelForCausalLM` for handling quantized saving and loading.
	Load the model using `AutoModelForCausalLM` for handling quantized saving and loading.