← Browse tools

Training & fine-tuning

PyTorch Lightning

Offers both a structured trainer and lower-level Fabric controls for scaling PyTorch workloads.

31,372 stars

Overview

Research summary

PyTorch Lightning separates model and training logic from repetitive execution infrastructure. Developers implement their model behavior in structured components while Lightning handles tasks such as accelerator placement, mixed precision and distributed training. The same repository includes Fabric for users who need more direct control over an existing PyTorch loop. These abstractions support experimentation and scaling without requiring every project to recreate the surrounding training engine. Lightning’s commercial cloud service is a separate offering from this Apache-licensed framework.

Repository summary

Stars
31,372
Open issues
Unavailable
Last push
2026-09-21
Commits, 90 days
Unavailable
Repository activity
Not scored
Version
Unavailable

Recorded catalogue figures. View repository data and provenance →

Classification

Pricing & services

Paid services unknown

Whether the provider offers paid products or services has not been established.

Licence scope

Implementation

Recorded implementation details and interfaces for PyTorch Lightning.

Implementation details

Python library and supporting tools

Languages
Python
Repository type
source

Recorded interfaces and capabilities

Licence scope

Repository

Repository snapshots, release information and recorded maintenance signals.

Repository snapshot

Lightning-AI/pytorch-lightning ↗

Stars
31,372
Open issues
Unavailable
Last push
2026-09-21
Commits, 90 days
Unavailable
Repository activity
Not scored
Archived
Not recorded

Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).

Maintenance and provenance

Catalogue snapshot
2026-10-06
Stars source
Recorded fallback
Last push source
Recorded fallback

Documentation

Recorded references and research provenance for this entry.

Recorded sources 5

Research metadata

Research date
2026-10-02
Catalogue snapshot
2026-10-06

Community & social 1 channels

Communities