Agent skill · Data & Analytics

pytorch-lightning

Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.

LeonChaoXgithub.com/LeonChaoXGitHub ↗
claude-codeships scriptsMIT
Install
npx skills add LeonChaoX/qinyan-academic-skills --skill pytorch-lightning --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 11
SKILL.md size: 7 KB
Bundled scripts: yes
Path: skills/09-机器学习与人工智能/pytorch-lightning/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 759
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# PyTorch Lightning ## Overview PyTorch Lightning is a deep learning framework that organizes PyTorch code to eliminate boilerplate while maintaining full flexibility. Automate training workflows, multi-device orchestration, and implement best practices for neural network training and scaling across multiple GPUs/TPUs. ## When to Use This Skill This skill should be used when: - Building, training, or deploying neural networks using PyTorch Lightning - Organizing PyTorch code into LightningModules - Configuring Trainers for multi-GPU/TPU training - Implementing data pipelines with LightningDataModules - Working with callbacks, logging, and distributed training strategies (DDP, FSDP, DeepSpeed) - Structuring deep learning projects professionally ## Core Capabilities ### 1. LightningModule - Model Definition Organize PyTorch models into six logical sections: 1. **Initialization** - `__init__()` and `setup()` 2. **Training Loop** - `training_step(batch, batch_idx)` 3. **Validation Loop** - `validation_step(batch, batch_idx)` 4. **Test Loop** - `test_step(batch, batch_idx)` 5. **Prediction** - `predict_step(batch, batch_idx)` 6. **Optimizer Configuration** - `configure_optimizers()` **Q

What's inside
Steps it walks through
  1. Overview
  2. When to Use This Skill
  3. Core Capabilities
  4. 1. LightningModule - Model Definition
  5. 2. Trainer - Training Automation
  6. 3. LightningDataModule - Data Pipeline Organization
  7. 4. Callbacks - Extensible Training Logic
  8. 5. Logging - Experiment Tracking
  9. 6. Distributed Training - Scale to Multiple Devices
  10. 7. Best Practices
  11. Quick Workflow
  12. Resources
  13. scripts/
  14. references/
Ships with 10 files
  • references/best_practices.md
  • references/callbacks.md
  • references/data_module.md
  • references/distributed_training.md
  • references/lightning_module.md
  • references/logging.md
  • references/trainer.md
  • scripts/quick_trainer_setup.py
  • scripts/template_datamodule.py
  • scripts/template_lightning_module.py
More from qinyan-academic-skills
All skills →
About this skill
What does the pytorch-lightning skill do?

Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.

How do I install it?

Run `npx skills add LeonChaoX/qinyan-academic-skills --skill pytorch-lightning --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From LeonChaoX/qinyan-academic-skills, a repository with 759 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going