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
Task
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
Job Opportunities
There are currently no job postings for this AI tool.
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