Build transformer fine-tuning run plans with task settings, hyperparameters, and model-card outputs. Use for repeatable Hugging Face or PyTorch finetuning workflows.
Scanned 6/2/2026
Install via CLI
openskills install majiayu000/claude-skill-registry---
name: dl-transformer-finetune
description: Build transformer fine-tuning run plans with task settings, hyperparameters, and model-card outputs. Use for repeatable Hugging Face or PyTorch finetuning workflows.
---
# DL Transformer Finetune
## Overview
Generate reproducible fine-tuning run plans for transformer models and downstream tasks.
## Workflow
1. Define base model, task type, and dataset.
2. Set training hyperparameters and evaluation cadence.
3. Produce run plan plus model card skeleton.
4. Export configuration-ready artifacts for training pipelines.
## Use Bundled Resources
- Run `scripts/build_finetune_plan.py` for deterministic plan output.
- Read `references/finetune-guide.md` for hyperparameter baseline guidance.
## Guardrails
- Keep run plans reproducible with explicit seeds and output directories.
- Include evaluation and rollback criteria.
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Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...