quark-onnx-autosearch-pro

quark-onnx-autosearch-pro is an MLOps & model serving skill for AI agents, published by amd in the Quark repository on GitHub. Skillspace rates quark-onnx-autosearch-pro D (62/100) and it passed the safety scan; the rating is based on static analysis only.

L3 recipe that runs `quark.onnx.AutoSearchPro` end-to-end on a user `.onnx` model: intake → preset selection (or custom search space) → calibration / eval data reader → standalone autosearch script generation → confirmed execution → best_params reporting. Wraps the Optuna-driven hyperparameter search exposed in `quark/onnx/quantization/auto_search/auto_search_pro.py`. Use when the user wants to "auto search", "tune quantization", "find best quant config", "sweep AdaRound/AdaQuant", "two-stage search", or pick `ADVANCED_SEARCH` / `XINT8_SEARCH` / `A8W8_SEARCH` / `A16W8_SEARCH` for an ONNX model. Not for single-shot PTQ (use `quark-onnx-ptq`). Not for safetensors models (use `quark-torch-ptq`).

Grade
D
Quality
62 / 100
Safety
Passed
GitHub stars
148

Unproven: rated by static analysis only, not yet compared head-to-head.

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View source on GitHubamd/Quark

Our review

Architecture
78 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
MIT
Adoption
Adopted by 0 other repositories, in 0 collections

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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