Model Compression: A Survey of Techniques

By Anwaar Khalid in Compression on Sat 10 August 2024

Machine Learning (ML) has witnessed a surge in interest in recent years driven by the availability of large-scale datasets, advances in ML frameworks such as PyTorch and TensorFlow, rise of hardware accelerators (e.g., GPUs and TPUs) that enable...

Case Study: Compressing DeepMind’s RepNet for Edge Deployment

By Anwaar Khalid in Compression on Mon 10 June 2024

In this case study, we explore compressing neural networks for efficient deployment on edge devices with limited resources. We explore practical techniques like quantization, pruning, and tensorization using off-the-shelf open-source tools. Our...