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quark-onnx-autosearch-pro

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UpdatedJuly 9, 2026 at 06:10

End-to-end Quark ONNX AutoSearchPro recipe — drives `quark.onnx.AutoSearchPro` (Optuna-based hyperparameter search) on a `.onnx` model to find the best quantization config (activation/weight spec, calibration method, CLE, AdaRound / AdaQuant, FastFinetune params). Use when the user wants to "auto search", "tune quantization", "find the best quant config", "sweep AdaRound/AdaQuant", "run AutoSearchPro / AutoSearch", "two-stage search", or pick one of the built-in presets (`ADVANCED_SEARCH`, `XINT8_SEARCH`, `A8W8_SEARCH`, `A16W8_SEARCH`) for their `.onnx` model. Not for HuggingFace / safetensors / PyTorch input models — use quark-torch-ptq instead. Not for single-shot ONNX PTQ without search — use quark-onnx-ptq.

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SKILL.md

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name

quark-onnx-autosearch-pro

description

Read and follow the instructions in .claude/skills-impl/l3-recipes/onnx/quark-onnx-autosearch-pro/SKILL.md.

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name

quark-onnx-autosearch-pro

description

Read and follow the instructions in .claude/skills-impl/l3-recipes/onnx/quark-onnx-autosearch-pro/SKILL.md.