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 camera for measuring sediment grain sizes with edge ML
An awesome list of "small but mighty" models and resources.
Notes and resources from Qualcomm On-device AI course, provided by DeepLearningAI
Python ML library for person fall detection. Intended for IoT deployments with on-device inference and on-device transfer learning.
Lightweight Attention U-Net for Breast Cancer Semantic Segmentation
A system for monitoring statistical data distribution shifts in distributed settings
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.
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