If your music is sounding a little mechanical, maybe it deserves a sprinkle of organic nurturing. We invite you to un-click the quantize!

Abstract: With ongoing advancements in natural language processing (NLP) and deep learning methods, the demand for computational and memory resources has considerably increased, which signifies the ...

Abstract: Quantizing neural network is an efficient model compression technique that converts weights and activations from floating-point to integer. However, existing model quantization methods are ...

Vector Post-Training Quantization (VPTQ) is a novel Post-Training Quantization method that leverages Vector Quantization to high accuracy on LLMs at an extremely low bit-width (<2-bit). VPTQ can ...

Segment Anything Model (SAM) has achieved impressive performance in many computer vision tasks. However, as a large-scale model, the immense memory and computation costs hinder its practical ...