train neural networks with joint quantization and pruning on both weights and activations using any pytorch modules

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Author: Xinyu Zhang, Ian Colbert, Srinjoy Das, Ken Kreutz-Delgado

Tags pytorch, quantization, pruning, model compression, neural network, machine learning

Requires: Python >=3.6

Project description

QSPARSE

License: MIT

Installation

QSPARSE can be installed from PyPI:

pip install qsparse

Usage

Documentation can be accessed from Read the Docs.

Examples of applying QSPARSE to different tasks are provided at examples and mdpi2022.

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Avatar for zxyml from gravatar.com zxyml

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View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

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Author: Xinyu Zhang, Ian Colbert, Srinjoy Das, Ken Kreutz-Delgado

Tags pytorch, quantization, pruning, model compression, neural network, machine learning

Requires: Python >=3.6


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2.0.1

This version

2.0.0

1.2.11

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1.2.8

1.2.7

1.2.6

1.2.5

1.2.4

1.2.3

1.2.2

1.2.1

1.2.0

1.1.0

1.0.1

1.0.0

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