ml-lightning-basics

Name: ml-lightning-basics
Author: nishide-dev

Comprehensive guide for PyTorch Lightning - LightningModule, Trainer, distributed training, PyTorch 2.0 torch.compile integration, Lightning Fabric, and production best practices

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Updated 2 months ago

View on GitHub ↗License: MIT

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PyTorch Lightning for ML Research

Overview

PyTorch Lightning is the industry-standard framework that organizes PyTorch code to decouple research from engineering. It eliminates boilerplate while maintaining full PyTorch flexibility, enabling researchers to focus on model logic rather than training infrastructure.

Key Benefits:

Eliminates 90% of boilerplate code
Automatic distributed training (DDP, FSDP, DeepSpeed)
Hardware agnostic (CPU, GPU, TPU, MPS)
Built-in best practice

[Description truncada. Veja o README completo no GitHub.]

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