This repository provides a custom MicroPython firmware that integrates TensorFlow Lite for Microcontrollers (TFLM), enabling TinyML inference on microcontrollers such as ESP32, RP2040, and STM32. It exposes a ‘microlite’ Python module with classes for loading TFLite models (interpreter, tensor) and an audio frontend for spectrogram extraction. The repo includes three pre-trained example applications: hello-world (sine regression), micro-speech (keyword spotting), and person detection (camera-based). The architecture is monolithic per board, built via CMake (ESP-IDF, RP2040 SDK) or Make (STM32). The build system and board definitions are deeply coupled to specific MicroPython and TFLM versions, and the code demonstrates careful memory management (custom GC heap allocators, arena buffer patterns) to run ML models on resource-constrained devices. While primarily a firmware/application project, it also contains pre-processed audio data and model files, giving it a slight hybrid nature. The codebase is functional and structured, but has several rough edges: duplicate model files, hardcoded source lists, and incomplete board support (STM32 noted as broken). It is actively maintained with CI workflows and recent commits, but technical drift is medium due to reliance on upstream main branches.