Choose the necessary framework dependencies to install based on your deploy environment. After successfully installing these packages, try your first quantization program. Following example code ...

Abstract: The huge memory and computing costs of deep neural networks (DNNs) greatly hinder their deployment on resource-constrained devices with high efficiency. Quantization has emerged as an ...

Abstract: Quantization is a critical technique employed across various research fields for compressing deep neural networks (DNNs) to facilitate deployment within resource-limited environments. This ...

A quantizer for advanced developers to quantize converted LiteRT models. It aims to facilitate advanced users to strive for optimal performance on resource demanding models (e.g., GenAI models). In a ...

Quantization is a method of reducing the size of AI models so they can be run on more modest computers. The challenge is how to do this while still retaining as much of the model quality as possible, ...