Pushing the Limit of Post-Training Quantization by Block Reconstruction
Pytorch implementation of BRECQ, ICLR 2021 @inproceedings{ li&gong2021brecq, title={BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction}, author={Yuhang Li and Ruihao Gong and Xu Tan and Yang Yang and Peng Hu and Qi Zhang and Fengwei Yu and Wei Wang and Shi Gu}, booktitle={International Conference on Learning Representations}, year={2021}, url={https://openreview.net/forum?id=POWv6hDd9XH} } Pretrained models We provide all the pretrained models and they can be accessed via torch.hub For example: use res18 = torch.hub.load(‘yhhhli/BRECQ’, model=’resnet18′, pretrained=True) to get the pretrained ResNet-18 […]
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