hpi-xnor/BMXNet-v2

BMXNet 2: An Open-Source Binary Neural Network Implementation Based on MXNet

43
/ 100
Emerging

This tool helps researchers and deep learning engineers develop and test neural networks that use binary or low-bit precision. It takes standard neural network architectures and converts their complex layers into more efficient, binarized versions, resulting in models that are smaller and faster for deployment. It is designed for those experimenting with efficient AI on resource-constrained devices or in situations requiring rapid inference.

232 stars. No commits in the last 6 months.

Use this if you are a deep learning researcher or engineer focused on creating efficient neural networks that can run on devices with limited computational power or memory.

Not ideal if you are looking for an off-the-shelf solution for high-precision deep learning tasks or if you are not comfortable with deep learning framework modifications.

efficient-AI deep-learning-optimization edge-AI model-compression neural-network-quantization
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 17 / 25

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Stars

232

Forks

32

Language

C++

License

Apache-2.0

Last pushed

May 20, 2022

Commits (30d)

0

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