Popular GitHub Repositories for Hardware Architectures

:robot: The free, Open Source alternative to OpenAI, Claude and others. Self-hosted and local-first. Drop-in replacement for OpenAI, running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. Features: Generate Text, Audio, Video, Images, Voice Cloning, Distributed, P2P inference

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

This repository offers a comprehensive collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like YOLO11, RT-DETR, SAM 2, Florence-2, PaliGemma 2, and Qwen2.5VL.

Intel® Nervana™ reference deep learning framework committed to best performance on all hardware

Semantic Segmentation Architectures Implemented in PyTorch

? Accelerate inference and training of ? Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools

A Curated list of IoT Security Resources

Massively parallel rigidbody physics simulation on accelerator hardware.

Open source neural network chess engine with GPU acceleration and broad hardware support.

Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning

Any model. Any hardware. Zero compromise. Built with @ziglang / @openxla / MLIR / @bazelbuild

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

A next-gen FOSS self-hosted unified zero trust secure access platform that can operate as a remote access VPN, a ZTNA/BeyondCorp architecture, API/AI gateway, a PaaS, an infrastructure for MCP & A2A architectures or even as an ngrok-alternative and a homelab infrastructure.

Self-hosted, local only NVR and AI Computer Vision software. With features such as object detection, motion detection, face recognition and more, it gives you the power to keep an eye on your home, office or any other place you want to monitor.

? Monitor deep learning model training and hardware usage from your mobile phone ?

This is originally a collection of papers on neural network accelerators. Now it's more like my selection of research on deep learning and computer architecture.

:unlock: Lip Reading - Cross Audio-Visual Recognition using 3D Architectures

A collection of state-of-the-art video or single-image super-resolution architectures, reimplemented in tensorflow.

Hardware for SUSI AI https://susi.ai

Synthetic data generators for tabular and time-series data