solo-learn is a self-contained library implementing various self-supervised learning algorithms (BYOL, SimCLR, MoCo, DINO, MAE, Barlow Twins, VICReg, SimSiam, SwAV) for unsupervised visual representation learning. It uses PyTorch Lightning for training, supports NVIDIA DALI for data loading, and allows using the trained backbones outside the library. The project provides SOTA implementations with training tricks and supports finetuning, mixing augmentations, and checkpointing.