# facebookresearch/barlowtwins

PyTorch implementation of Barlow Twins.

Repository: https://github.com/facebookresearch/barlowtwins
Canonical: https://ross.abutalabs.com/products/barlowtwins
Language: Python
License: MIT
License Family: permissive
Archived: true
Last push: 2022-03-03T02:59:31+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2008, "days_push": 1644, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1017, forks 131 (observed 2026-08-28T04:03:14.677874+00:00)

## What it is
A PyTorch implementation of Barlow Twins, a self-supervised learning method that trains visual representations by reducing redundancy between embeddings of two augmented views of an image. It includes training and evaluation scripts for ImageNet plus a pretrained ResNet-50 available via PyTorch Hub.

## Use cases
- train self-supervised image representations with Barlow Twins
- download a pretrained ResNet-50 backbone for transfer learning
- evaluate self-supervised features with linear probing on ImageNet
- reproduce the Barlow Twins paper results
- run semi-supervised finetuning with limited labels
- learn how self-supervised learning via redundancy reduction works

## When to choose
- you want to reproduce or build on the Barlow Twins paper
- you need a pretrained self-supervised ResNet-50 backbone in PyTorch
- you are researching self-supervised representation learning methods

## When to avoid
- you need a maintained library with frequent updates and broad model support
- you lack multi-GPU resources, since full training takes ~7 days on 16 V100s
- you want a general-purpose SSL framework rather than a single-method reference implementation

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning
- domain: machine-learning, computer-vision, deep-learning
- platform: python
- tags: self-supervised-learning, pytorch, representation-learning, research-code, pretrained-models, resnet, gpu, linux

## Member repositories
- facebookresearch/barlowtwins (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:14.677874+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:11:12.004807+00:00, confidence not recorded.
  - readme: https://github.com/facebookresearch/barlowtwins (fetched 2026-08-28T04:03:14.677874+00:00, sha 7b4b4424c780)
- Data as of 2026-08-30T08:39:29.467469+00:00.