5 datasets found

ILMPQ: An Intra-Layer Multi-Precision Deep Neural Network Quantization framework for FPGA

Large Language Models (LLMs) have greatly advanced the natural language processing paradigm. However, the high computational load and huge model sizes pose a grand challenge for...

TensorQuant toolbox is used to apply fixed point quantization to DNNs. The simulations are focused on popular CNN topologies, such as Inception V1, Inception V3, ResNet 50 and...

The proposed method, called LSQ+, extends LSQ [7] by adding a simple yet effective learnable offset parameter for activation quantization to recover the lost accuracy on...

Learning to synthesize data has emerged as a promising direction in zero-shot quantization (ZSQ), which represents neural networks by low-bit integer without accessing any of...