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Signed-off-by: yiliu30 <yi4.liu@intel.com>
Signed-off-by: yiliu30 <yi4.liu@intel.com>
Signed-off-by: yiliu30 <yi4.liu@intel.com>
Signed-off-by: yiliu30 <yi4.liu@intel.com>
Signed-off-by: yiliu30 <yi4.liu@intel.com>
Signed-off-by: yiliu30 <yi4.liu@intel.com>
Signed-off-by: yiliu30 <yi4.liu@intel.com>
Signed-off-by: yiliu30 <yi4.liu@intel.com>
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Summary of ChangesHello @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 primarily focuses on improving the clarity and organization of the AutoRound quantization documentation, making it easier for users to understand its capabilities and configurations. Additionally, it introduces a new parameter to enhance the flexibility of the AutoRound tuning process. Highlights
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Code Review
This pull request significantly refactors the AutoRound documentation by creating a main README.md with general information and moving the specific quickstart guide into a subdirectory. It also adds a new lr parameter to the AutoRoundModifier. My review focuses on improving the clarity and correctness of the new documentation. I've found a broken link, some typos, and formatting issues that should be addressed to improve the user experience.
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/gemini review |
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Code Review
This pull request refactors the documentation for AutoRound, improving its structure and clarity. The main README now serves as a high-level guide, covering when to use AutoRound, its key parameters, and different quantization configurations. The detailed quickstart guide and code walkthrough have been moved to a new, more appropriate location within the quantization_w4a16 example directory. A small code change adds support for a configurable learning rate (lr) in the AutoRoundModifier, which is also reflected in the new documentation. My review includes a few suggestions to fix minor typos and incorrect links in the updated documentation to ensure its accuracy.
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/gemini review |
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Code Review
This pull request refactors the AutoRound documentation, providing a more structured and comprehensive overview in the main README.md and moving the quickstart guide to a subdirectory. It also introduces a new lr parameter to the AutoRoundModifier to allow for learning rate configuration. The changes are well-structured and improve the documentation's clarity. I've suggested a few fixes in the README.md file to correct a broken link and a couple of typos.
| ## Quickstart | ||
| ## When to Use AutoRound | ||
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| In summary, AutoRound demonstrates leading or on-par performance at 4-bit precision, with clear advantages for sub-4-bit, as reported in **SignRoundV1** ([paper](https://arxiv.org/pdf/2309.05516)), **SignRoundV2** ([paper](http://arxiv.org/abs/2512.04746)) and the **Intel Low-Bit Open LLM Leaderboard** ([link](https://huggingface.co/spaces/Intel/low_bit_open_llm_leaderboard)), |
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The link to the SignRoundV2 paper appears to have a typo. The year 2512 is likely incorrect. Based on a search on arXiv, the correct ID seems to be 2312.04746. Please correct the link to ensure it points to the correct paper.
| In summary, AutoRound demonstrates leading or on-par performance at 4-bit precision, with clear advantages for sub-4-bit, as reported in **SignRoundV1** ([paper](https://arxiv.org/pdf/2309.05516)), **SignRoundV2** ([paper](http://arxiv.org/abs/2512.04746)) and the **Intel Low-Bit Open LLM Leaderboard** ([link](https://huggingface.co/spaces/Intel/low_bit_open_llm_leaderboard)), | |
| In summary, AutoRound demonstrates leading or on-par performance at 4-bit precision, with clear advantages for sub-4-bit, as reported in **SignRoundV1** ([paper](https://arxiv.org/pdf/2309.05516)), **SignRoundV2** ([paper](http://arxiv.org/abs/2312.04746)) and the **Intel Low-Bit Open LLM Leaderboard** ([link](https://huggingface.co/spaces/Intel/low_bit_open_llm_leaderboard)), |
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