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
Categories
Transformer ModelsLicense
MIT LicenseFollow solo-learn
You Might Also Like
MongoDB Atlas runs apps anywhere
MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of solo-learn!