🚀 Lightning-fast computer vision models. Fine-tune SOTA models with just a few lines of code. Ready for cloud ☁️ and edge 📱 deployment.

CIFNet: A lightweight, single-pass Class Incremental Learning model designed for edge devices. Minimizes training time, energy consumption, and memory usage, making it ideal for real-time, resource-constrained environments.

This repository contains the code and data of the paper titled "FrugalPrompt: Reducing Contextual Overhead in Large Language Models via Token Attribution."

🧠 Official implementation of FedHENet: A frugal, one-shot federated learning framework for heterogeneous environments. Privacy-preserving via HE, energy-efficient, and hyperparameter-free. Accepted at ESANN 2026.

PyTorch implementation of the "Reducing inference energy consumption using dual complementary CNNs" paper published in FGCS journal.

A curated collection of Edge AI courses for everyone

Maximizing LLM tokens/sec on Jetson under limited memory

An open and practical guide to Edge Language

This repository contains the PyTorch implementation of the paper "Selecting Images With Entropy For Frugal Knowledge Distillation'" published in IEEE Access.

A production-ready, frugal, sovereign AI system that orchestrates India's open-source language models to achieve state-of-the-art reasoning on consumer hardware through Test-Time Compute (TTC) and Cognitive Serialization.

An open and practical guide to Edge Audio.