Abstract: Modern datasets often exhibit heavy-tailed behavior, while quantization is inevitable in digital signal processing and many machine learning problems. This paper studies the quantization of ...

Abstract: Model quantization is essential to deploy deep convolutional neural networks (DCNNs) on resource-constrained devices. In this article, we propose a general bitwidth assignment algorithm ...

integrations with tools such as bitsandbytes (4-bit quantization), PEFT (parameter efficient fine-tuning), and Flash Attention 2 utilities and helpers to run generation with the model mechanisms to ...

AI competition accelerates globally as nations, companies, and militaries race to shape emerging technological power.

Among these techniques, Post-Training Quantization (PTQ) has emerged as a subject of considerable interest due to its noteworthy compression efficiency and cost-effectiveness in the context of ...