VISSL
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About
VISSL is a library for state-of-the-art self-supervised learning from images. It is built on top of PyTorch and allows using all of its components. It provides reproducible reference implementation of SOTA self-supervision approaches (like SimCLR, MoCo, PIRL, SwAV etc) and their components that can be reused. Also supports supervised trainings. It includes a variety of benchmarks tasks (linear image classification, full finetuning, semi-supervised, low-shot, nearest neighbor, object detection) available to evaluate models. It is easy to train model on 1-gpu, multi-gpu and multi-node. Seamless scaling to large scale data and model sizes with FP16, LARC etc
Platform
Task
Features
• fp16, larc support
• scalable training on 1-gpu, multi-gpu and multi-node
• variety of benchmarks tasks
• reproducible reference implementation of sota self-supervision approaches
• sota self-supervision methods
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