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VISSL

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About

VISSL is a PyTorch-powered library developed by Facebook Research, providing state-of-the-art self-supervised learning from images. It offers reproducible reference implementations of various SOTA self-supervision approaches like SimCLR, MoCo, PIRL, and SwAV, and also supports supervised trainings. The library includes a variety of benchmark tasks for model evaluation, such as linear image classification, full finetuning, semi-supervised, low-shot, nearest neighbor, and object detection. VISSL is designed to be highly scalable, allowing easy training on 1-GPU, multi-GPU, and multi-node setups, with seamless scaling to large data and model sizes using features like FP16 and LARC.

Platform
Web
Task
model training

Features

sota self-supervision methods

fp16 and larc support

powered by pytorch

scalable (1-gpu, multi-gpu, multi-node)

variety of benchmark tasks

support for supervised trainings

reproducible reference implementation

Pricing Plans

Free
Free Plan

State-of-the-art self-supervised learning methods

Reproducible reference implementations (SimCLR, MoCo, PIRL, SwAV)

Support for supervised trainings

Variety of benchmark tasks

Scalable training (1-gpu, multi-gpu, multi-node)

FP16 and LARC support

Community support via GitHub

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