6 tagged hyperparameter-optimization, measured the same way as everything else here.
Skill Claude CodeCodex
Use when the user wants to optimize configurable system parameters against a measurable scalar objective, especially for model training, inference, quantitative strategies, reinforcement learning, scientific workflows, or other expensive black-box evaluations where reading the project can improve trial selection.
Plugin Claude Code
Optimize configurable systems against measurable objectives.
Instructions file
Instructions for Axect/pytorch_template, covering pytorchtemplate, migration skill maintenance rule, when adding a new feature, when modifying an existing feature and development workflow.
Skill Claude CodeCodex
Migrate an existing project that uses pytorchtemplate to the latest version. Use this skill when the user says: "update template", "migrate", "upgrade", "apply latest changes", "sync with template", "update pytorchtemplate", or when the user's project is missing new features (preflight, hpo-report, data field…
Skill Claude CodeCodex
Guide for training PyTorch models using this template's config-driven pipeline. Use this skill whenever the user wants to: train a model, create experiment configs (run.yaml / opt.yaml / best.yaml), run hyperparameter optimization (HPO) with Optuna, extract best parameters from an HPO study, set up a new experiment…