Quantization in Depth lets you build and customize your own linear quantizer from scratch, going beyond standard open source libraries such as PyTorch and ...

Quantization is a technique to reduce the computational and memory costs of running inference by representing the weights and activations with low-precision ...

26 мая 2023 г. · Quantization Aware Training is a technique used in deep learning to simulate the impact of quantization on a neural network during the training ...

22 сент. 2023 г. · Quantization in general can be defined as mapping values from a large set of real numbers to values in a small discrete set.

29 июл. 2024 г. · Quantization is the process of reducing the precision of a digital signal, typically from a higher-precision format to a lower-precision format.

Discover how to quantize open source models using Hugging Face Transformer and Quanto library. Master linear quantization.

23 авг. 2023 г. · A Qualcomm expert breaks down some of the tools and techniques they use to fit GenAI models on a smartphone.

Using the Deep Learning Toolbox Model Quantization Library support package, you can quantize a network to use 8-bit scaled integer data types. To learn about ...

Quantization involves reducing the precision of the model's weights and activations, typically from floating-point numbers to integers. Topology optimization ...

We provide practical guidance on quantization and pruning. This paper focuses primarily on network optimization for convolutional neural networks. It is ...