A library of self-supervised methods for visual representation learning powered by Pytorch Lightning. A library of self-supervised methods for unsupervised visual representation learning powered by PyTorch Lightning. We aim at providing SOTA self-supervised methods in a comparable environment while, at the same time, implementing training tricks. The library is self-contained, but it is possible to use the models outside of solo-learn.

Features

  • Increased data processing speed by up to 100% using Nvidia Dali
  • Flexible augmentations
  • Online linear evaluation via stop-gradient for easier debugging and prototyping (optionally available for the momentum backbone as well)
  • Standard offline linear evaluation
  • Online and offline K-NN evaluation
  • Automatic feature space visualization with UMAP

Project Samples

solo-learn Screenshot 1

Project Activity

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Categories

Transformer Models

License

MIT License

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Additional Project Details

Programming Language

Python

Related Categories

Python Transformer Models

Registered

2023-04-21
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