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dl-transformer-finetune

Build transformer fine-tuning run plans with task settings, hyperparameters, and model-card outputs. Use for repeatable Hugging Face or PyTorch finetuning workflows.

3,556 stars

byopenclaw

View on GitHub Installation ↓

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/dl-transformer-finetune/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/0x-professor/dl-transformer-finetune/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/dl-transformer-finetune/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How dl-transformer-finetune Compares

Feature / Agent	dl-transformer-finetune	Standard Approach
Platform Support	multi	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Build transformer fine-tuning run plans with task settings, hyperparameters, and model-card outputs. Use for repeatable Hugging Face or PyTorch finetuning workflows.

Which AI agents support this skill?

This skill is compatible with multi.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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.