pytorch-lightning
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
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Decision brief
PyTorch Lightning scales PyTorch models across GPUs with minimal code changes.
Good fit when
- Scalable ML model training with consistent API across single to multiple GPUs
- Zero-code-change requirement when expanding from one GPU to many, including up to 10,000+ GPUs
Avoid when
- For lightweight models requiring minimal configuration or manual control over model distribution
- Projects that target environments without access to multi-GPU setups and do not require scalability features
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- No criticals
- As of 1mo
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Install
pip install pytorch-lightningHow it fits your stack(1)
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Evidence and technical details
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Overview
A framework for training and serving machine learning models, supporting PyTorch models to scale with ease on multiple GPUs.
Capability facts
- Languages
- python
Source: github.language+pyproject.toml · Aug 3, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Tags
README
Quick start
Install Lightning:
pip install lightning
Advanced install options
Install with optional dependencies
pip install lightning['extra']
Conda
conda install lightning -c conda-forge
Install stable version
Install future release from the source
pip install https://github.com/Lightning-AI/lightning/archive/refs/heads/release/stable.zip -U
Install bleeding-edge
Install nightly from the source (no guarantees)
pip install https://github.com/Lightning-AI/lightning/archive/refs/heads/master.zip -U
or from testing PyPI
pip install -iU https://test.pypi.org/simple/ pytorch-lightning
! pip install torchvision
import torch, torch.nn as nn, torch.utils.data as data, torchvision as tv, torch.nn.functional as F import lightning as L
For agents
This page has a .md twin and JSON over the API.