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[P] Larq, an Open-Source Library for Training Binarized Neural Networks

Hi all, I’m working for Plumerai, a London-based startup that is developing hardware for binarized neural networks (BNN). BNNs are designed to make neural networks much more efficient, so that it becomes feasible to use them in embedded applications such as self-driving cars and mobile phones.

Over the past few months we’ve been developing Larq, an open source library to make it easier for researchers and developers to work with BNNs. We have also reproduced a number of key papers in the field and made pretrained BNNs available in Larq-Zoo (Bi-Real Net, XNOR-net, BinaryNet), and we’ll soon add more. The library is built on top of tensorflow.keras. Larq has already been very valuable to us in our own research (we recently made our first paper available on arxiv – it even got some attention on this subreddit!), and we are now at a point where we are very eager to share it with others.

If you’re interested in this space, please have a look and let us know what you think!

Documentation: https://larq.dev/

GitHub Larq: https://github.com/larq/larq

GitHub Larq-Zoo: https://github.com/larq/zoo

submitted by /u/khelwegen
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.