qkerasV3 is an open-source library compatible with Keras 3, focused on quantization-aware training and model compression. It helps machine learning engineers optimize neural networks for efficient deployment, especially on edge and embedded devices.
In the Infrastructure & Backend space, qkerasV3 Documentation takes a focused approach. It focuses on enabling efficient quantization and compression of neural networks for deployment on resource-constrained devices. qkerasV3 Documentation is an open-source project aimed at machine learning engineers. The project is open source (Apache-2.0). qkerasV3 Documentation is available on the web, the command line, and API, and it can be self-hosted.
qkerasV3 contributors builds and maintains qkerasV3 Documentation, and the product first shipped in 2019. The project is developed in the open on GitHub with 13 commits in the last 90 days. Among its 5 catalogued features are quantization-aware training, model compression, and keras 3 compatible. It exposes integrations via a public API.
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