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@dsikka dsikka commented Oct 18, 2025

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

Note: This is required to complete the testing suite, please only add the label once the PR is code complete and local testing has been performed.

@dsikka dsikka added ready When a PR is ready for review qwen For any PR / issue related to Qwen support labels Oct 18, 2025
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Summary of Changes

Hello @dsikka, 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 focuses on improving the clarity and accuracy of an example file by correcting a misleading comment. The change ensures that the inline documentation correctly describes the NVFP4 quantization scheme, which involves fp4 weights and activations, rather than an fp8 scheme as previously stated. This is a minor but important documentation fix for the Qwen3 VL MoE example.

Highlights

  • Documentation Correction: Updated an outdated comment in the qwen3_vl_moe_w4a4_fp4.py example to accurately reflect the quantization scheme being used. The comment previously described an fp8 quantization, but now correctly states fp4 quantization for weights and activations.
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Code Review

This pull request updates a comment in the Qwen3-VL-MoE quantization example to accurately describe the quantization scheme being applied. The previous comment incorrectly stated that FP8 quantization was used, while the code uses the NVFP4 scheme. The change corrects this to FP4 with group-wise quantization for weights and dynamic group activations. Additionally, a note about data-free quantization being the only supported method was removed, which is correct as the example uses a calibration dataset. The change improves the clarity and correctness of the example code.

@dsikka dsikka enabled auto-merge (squash) October 18, 2025 11:38
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