Distributed 56M-parameter LLM inference across 3 ESP32-S3 boards via ESP-NOW , Split-PLE + KV cache, fully offline.

A list of production-ready models for resource-constrained devices.

An open and practical guide to Edge AI Engineering.

Official library of pre-optimized Tensorbit models. Ready-to-deploy LLMs and Vision Transformers for edge hardware, optimized via the Tensorbit P-D-Q pipeline.

Run a 56M-parameter language model across three ESP32-S3 boards using ESP-NOW for distributed inference.

TinyML-based IoT system for electric motor fault detection using Edge Impulse and TensorFlow Lite Micro.

Edge-GNN: Constraint-aware graph neural networks for biological interaction modeling under edge deployment constraints (computational oncology, PPI networks).