Quantizing Diffusion Models from a Sampling-Aware Perspective
Published in ArXiv.org • May 4, 2025
NobleIDNI4P80W74R12S66
Authors:,,
Qian Zeng
Jie Song
Yuanyu Wan
Abstract
Diffusion models have recently emerged as the dominant approach in visual generation tasks. However, the lengthy denoising chains and the computationally intensive noise estimation networks hinder their applicability in low-latency and resource-limited environments. Previous research has endeavored ...
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