Abstract: In this paper, we propose a quantization approach, as an alternative of sparsification, to curb the growth of the radial basis function structure in kernel adaptive filtering. The basic idea ...

Abstract: As deep neural networks have been performing better and better on various tasks, their number of parameters has been increasing, and the demand for computing power and storage has been ...

To support int8 model deployment on mobile devices,we provide the universal post training quantization tools which can convert the float32 model to int8 model. mean and norm are the values you passed ...

Large language models (LLMs) show excellent performance but are compute- and memory-intensive. Quantization can reduce memory and accelerate inference. However, for LLMs beyond 100 billion parameters, ...