An enterprise-ready and vendor-agnostic federated learning platform.

In this repository, we explore model compression for transformer architectures via quantization. We specifically explore quantization aware training of the linear layers and demonstrate the performance for 8 bits, 4 bits, 2 bits and 1 bit (binary) quantization.

A lightweight, resource-efficient MLOps monitoring solution for machine learning models deployed on edge devices. Features system health tracking, model I/O logging, drift detection, and cloud telemetry.