Popular GitHub Repositories for Embedded

DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.

MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba. Full multimodal LLM Android App:[MNN-LLM-Android](./apps/Android/MnnLlmChat/README.md)

Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

PaddlePaddle High Performance Deep Learning Inference Engine for Mobile and Edge (飞桨高性能深度学习端侧推理引擎）

Speech-to-text, text-to-speech, speaker diarization, speech enhancement, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, HarmonyOS, Raspberry Pi, RISC-V, x86_64 servers, websocket server/client, support 11 programming languages

Tengine is a lite, high performance, modular inference engine for embedded device

On-device AI across mobile, embedded and edge for PyTorch

Top2Vec learns jointly embedded topic, document and word vectors.

A Curated list of IoT Security Resources

Introduction to Machine Learning Systems

? Gracefully face hCaptcha challenge with MoE(ONNX) embedded solution.

TinyML AI inference library

Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0

An Embedded Computer Vision & Machine Learning Library (CPU Optimized & IoT Capable)

Hardware for SUSI AI https://susi.ai

JVector: the most advanced embedded vector search engine

A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

A higher-level Neural Network library for microcontrollers.

A lightweight, simple-to-use, RNN wake word listener

This is a list of interesting papers and projects about TinyML.