executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
lora_parameter_budgetCompute LoRA trainable parameter budgets and reduction ratios for adapted Transformer projections.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this skill to estimate how many task-specific parameters LoRA trains compared with full fine-tuning.
Projection dimensions or d_model, rank r, adapted matrix count, layer count, and optional full-parameter baseline.
Trainable LoRA count, dense-update count for the same matrices, and reduction ratios.
For square Transformer projections use the paper formula 2 * L_hat * d_model * r, where L_hat counts adapted matrices. Compare against full dense updates L_hat * d_model * d_model.
Run included tests for formula correctness and rank monotonicity.
This is an accounting skill; it does not measure wall-clock training throughput.