BWRF improves quantization-aware training by grafting full-precision blocks onto the low-precision model during training, producing mixed-precision guides that raise ImageNet and CIFAR-10 accuracy at 2 to 4 bits.
Low-bit quantization of neural networks for efficient inference
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Improving Quantization-aware Training of Low-Precision Network via Block Replacement on Full-Precision Counterpart
BWRF improves quantization-aware training by grafting full-precision blocks onto the low-precision model during training, producing mixed-precision guides that raise ImageNet and CIFAR-10 accuracy at 2 to 4 bits.