quantization-aware fine-tuning
Quantization-aware fine-tuning refers to the process of optimizing a neural network that has been previously quantized. It involves fine-tuning the network's weights while considering the impact of quantization, which is the process of reducing the precision of the network's weights and activations to a smaller number of bits. By incorporating quantization-aware techniques during the fine-tuning phase, the network's performance can be improved while preserving the benefits of low-precision quantization.
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