[Audio] Qwen2 Audio Example

[kylesayrs]

Purpose

• Support qwen2_audio, which previously could not be supported due to accelerate offloading

[gemini-code-assist]

Summary of Changes

Hello @kylesayrs, 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 introduces a new example showcasing the application of 4-bit GPTQ quantization to the Qwen2-Audio-7B model, detailing the entire process from data loading and preprocessing to model generation and saving. Concurrently, an existing Llama3 quantization example has been temporarily disabled by commenting out its core functionality and changing its target model, likely to streamline development or testing efforts related to the new audio model integration.

Highlights

• New Qwen2 Audio Example: A new example script, qwen2_audio.py, has been added to demonstrate 4-bit quantization (W4A16 GPTQ) of the Qwen2-Audio-7B model using the llmcompressor library.
• Audio Data Preprocessing: The new example includes comprehensive steps for loading and preprocessing audio data from the MLCommons/peoples_speech dataset, preparing it for the Qwen2-Audio model's input requirements.
• Llama3 Example Modifications: The existing llama3_example.py script has been updated to change its target model to bigcode/starcoder2-3b and to comment out the quantization recipe, generation, and saving steps, effectively disabling its core functionality for now.

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[github-actions]

👋 Hi! Thank you for contributing to llm-compressor. Please add the ready label when the PR is ready for review.

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[gemini-code-assist]

Code Review

This pull request introduces a new example script for quantizing the Qwen2 Audio model and modifies an existing Llama3 example. The new script is a valuable addition, but it appears to be a work in progress, with some key functionality commented out and using temporary values for quick testing. My review focuses on suggestions to make the new example script fully functional and improve its code quality. Specifically, I recommend uncommenting the main oneshot call, using a more appropriate number of calibration samples for effective quantization, and adopting a more idiomatic approach for tensor manipulation.

[brian-dellabetta]

nice!

[mergify]

The quality checks have failed. Please run make style and make quality under
the root directory to adddress the lint failures. You will need to install the
dev optional install to get the required linting packages:
https://github.com/vllm-project/llm-compressor/blob/main/CONTRIBUTING.md