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Awesome GitHub RepositoriesMoCo Implementations
Implementations of the Momentum Contrastive (MoCo) framework for self-supervised learning.
Distinct from Machine Learning Implementations: Focuses specifically on the MoCo momentum-encoder and memory-bank architecture, not general ML algorithms.
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Awesome MoCo Implementations GitHub Repositories
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- lightly-ai/lightly
lightly-ai/lightly
3,684Auf GitHub ansehenLightly is a self-supervised learning framework and computer vision data curation tool designed to manage large image datasets and train models on unlabeled data. It functions as a PyTorch vision library and dataset management SDK, providing tools to convert raw images into high-dimensional vectors for similarity search, visualization, and feature extraction. The project implements a variety of self-supervised architectures, including MoCo, SimCLR, VICReg, Barlow Twins, and masked image modeling. It distinguishes itself by combining these learning frameworks with active learning capabilities,
Provides a full implementation of the MoCo model utilizing momentum encoders and memory banks.
Pythoncomputer-visioncontrastive-learningcontributions-welcome
