Individual skill
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.
skills/pytorch-lightning/SKILL.md
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SKILL.mdcore · 7,494 bytesSKILL.mdcore · 7,494 bytesSKILL.mdcore · 7,494 bytesSKILL.mdcore · 7,494 bytesreferences/best_practices.mddoc · 16,071 bytesreferences/callbacks.mddoc · 15,540 bytesreferences/data_module.mddoc · 14,497 bytesreferences/distributed_training.mddoc · 14,213 bytesreferences/lightning_module.mddoc · 13,728 bytesreferences/logging.mddoc · 14,259 bytesreferences/trainer.mddoc · 14,784 bytesscripts/__pycache__/quick_trainer_setup.cpython-313.pycasset · 9,414 bytesscripts/__pycache__/template_datamodule.cpython-313.pycasset · 9,690 bytesscripts/__pycache__/template_lightning_module.cpython-313.pycasset · 6,916 bytesscripts/quick_trainer_setup.pyruns · 12,985 bytesscripts/template_datamodule.pyruns · 9,354 bytesscripts/template_lightning_module.pyruns · 5,886 bytes
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# 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)