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Training & fine-tuning

PyTorch

Combines eager tensor programming with automatic differentiation and an extensive model-development ecosystem.

103,608 stars

Overview

Research summary

PyTorch provides tensor operations, automatic differentiation and neural-network building blocks for training and executing machine-learning models. Its Python-first workflow integrates with the scientific Python ecosystem while accelerator backends handle numerical computation. Developers can define custom model architectures and training loops, then build on distributed and optimization tooling in the wider PyTorch ecosystem. It is foundational infrastructure for many model adaptation and serving projects, rather than an agent framework or a packaged collection of pretrained model weights.

Repository summary

Stars
103,608
Open issues
Unavailable
Last push
2026-10-02
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.

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

pytorch/pytorch ↗

Stars
103,608
Open issues
Unavailable
Last push
2026-10-02
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

Video