This article explores the potential of compact language models, which are smaller versions of large language models that offer scalability, accessibility, and efficiency to…
Browsing: Quantization
This paper proposes a two-layer accumulated quantized compression algorithm (TLAQC) to reduce the communication cost of federated learning. TLAQC introduces a revised quantization method…
MATLAB and Simulink can be used to create optimised code for full AI applications, including pre- and post-processing algorithms, for use on CPUs, GPUs,…
Model Compression Toolkit (MCT) is an open-source project for neural network model optimization under efficient, constrained hardware. This project provides researchers, developers, and engineers…