This repository provides a PyTorch implementation of MoCo (Momentum Contrast), a self-supervised learning approach for visual representation learning. The method uses a queue-based dictionary and momentum-updated encoder to learn feature representations without labels. It achieves competitive results on downstream tasks like linear classification and object detection by training on unlabeled images.