计划执行与检查节点
executing-plans
按既定实施计划完成工作,保持过程检查和反馈。
autovp_training_loop【效率与协作】Run a reduced AutoVP prompt optimization step while proving the source classifier remains frozen.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this skill to recover or test AutoVP's parameter-efficient adaptation mechanism. It is appropriate when a frozen classifier callable, prompt module, label mapper, and small dataset are available.
Training examples, labels, prompt parameters, frozen classifier weights/callable, label mapping, learning rate, and step count.
Loss before/after, prompt parameters before/after, classifier frozen check, predictions, and accuracy.
Apply visual prompt, run frozen classifier, map logits to targets, compute loss, update only prompt or mapping parameters, and record trace evidence. Never mutate source classifier weights.
Run included tiny deterministic optimizer test.