Nader Bouacida

PTQ4ADM: Post-Training Quantization for Efficient Text Conditional Audio Diffusion Models

Denoising diffusion models have emerged as state-of-the-art in generative tasks across image, audio, and video domains, producing high-quality, diverse, and contextually relevant data. However, their broader adoption is limited by high computational costs and large memory footprints. Post-training q…