Pytorch Lightning
Steer an agent through PyTorch Lightning training loops, trainers, and module structure when you are building or refactoring ML experiments.
Overview
Pytorch-lightning is an agent skill for the Build phase that helps solo builders apply PyTorch Lightning training patterns when implementing ML backends and experiments.
Install
npx skills add https://github.com/orchestra-research/ai-research-skills --skill pytorch-lightningWhat is this skill?
- Research-stack skill for PyTorch Lightning experiment patterns
- Suited to structuring Trainer, LightningModule, and DataModule conventions
- Fits solo builders prototyping ML features without a full platform team
- Pairs with other orchestra-research AI skills for end-to-end research workflows
- Sparse upstream SKILL.md—pair with official Lightning docs for version-specific APIs
Adoption & trust: 1 installs on skills.sh; 9.4k GitHub stars; 2/3 security scanners passed (skills.sh audits).
What problem does it solve?
You are writing PyTorch training code and want Trainer/LightningModule structure without re-deriving best practices from scratch in every chat.
Who is it for?
Indie ML builders and small research repos standardizing on PyTorch Lightning for fine-tuning or custom model training.
Skip if: Pure inference-only APIs with no training loop, or teams standardized on bare PyTorch/JAX who will not adopt Lightning.
When should I use this skill?
Building or refactoring PyTorch Lightning training code in a research or product ML backend.
What do I get? / Deliverables
Your agent proposes Lightning-aligned module boundaries, training entrypoints, and refactor steps that match common research-project layouts.
- LightningModule and training script scaffolding
- Trainer configuration recommendations
Recommended Skills
Journey fit
Model training code is authored in Build; this skill targets implementation of research pipelines rather than market validation or ops monitoring. Training scripts, LightningModules, and callbacks are backend/research engineering work even when notebooks are involved.
How it compares
Training-framework workflow skill—not a hosted training platform or AutoML product integration.
Common Questions / FAQ
Who is pytorch-lightning for?
Solo builders and researchers using coding agents to implement or refactor PyTorch Lightning training code in small repos.
When should I use pytorch-lightning?
During Build while scaffolding LightningModule classes, Trainer configuration, or migrating messy PyTorch scripts into Lightning structure.
Is pytorch-lightning safe to install?
Check the Security Audits panel on this Prism page for the orchestra-research package; training skills may imply running local GPU jobs you control separately.
SKILL.md
READMESKILL.md - Pytorch Lightning
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