Improved Quantization for Neural Networks: Adaptive Block Scaling in NVFP4

This research explores enhancements to the NVFP4 quantization technique, a method for compressing neural network parameters. The adaptive block scaling strategy promises to improve accuracy in quantized models, making them more efficient for deployment.

• •Addresses the challenge of reducing the computational cost and memory footprint of neural networks.
• •Introduces an adaptive block scaling method to improve the accuracy of NVFP4 quantization.
• •Potential for more efficient deployment of neural networks on resource-constrained devices.