Node-graph GUI and Python backend for running diffusion models to generate images, video, 3D, and audio locally.
Python library that runs large language model inference layer by layer, so 70B-class models fit on a single 4GB GPU without quantization.
A free, MIT-licensed course of 542 lessons on AI engineering, implementing model internals, retrieval, and agent runtimes from scratch.
Framework where coding agents discover and refine robot sensorimotor skills as reusable code in place of gradient-based training.
Native macOS and Apple Silicon inference server exposing OpenAI, Anthropic and Ollama APIs, with a Swift app, written in Zig.
Open-source AI-oriented quantitative investment platform covering data, strategy research, backtesting, simulated and live trading.
A 12-week, 24-lesson beginner curriculum covering AI fundamentals, neural networks, computer vision, NLP, and AI ethics with TensorFlow and PyTorch labs.
Inference code, checkpoints, and notebooks for Meta's Segment Anything Model (SAM), which produces object masks from points, boxes, or automatically for whole images.
PyTorch library for audio generation research, providing inference and training code for MusicGen, AudioGen, and EnCodec.
Reference code for Stable Diffusion, a latent text-to-image diffusion model that generates images from text prompts.
Official C++ inference framework for 1-bit (1.58-bit) LLMs, providing optimized CPU and GPU kernels.
Open-source SDK for building and running AI agents in Python and TypeScript, with a fully assembled harness and a model-agnostic agent loop.
Desktop and CLI tool that trains 3D Gaussian Splatting models from photos or video, then exports splats and textured meshes, using Vulkan compute.
A free, cohort-based course teaching ML engineering: training models, exposing them via APIs, and deploying with Docker, Kubernetes, and AWS Lambda.
C/C++ inference engine for diffusion image and video models such as SD, Flux, Wan, and Qwen-Image, built on ggml.
A library of model optimization techniques (quantization, pruning, distillation, NAS, speculative decoding, sparsity) that exports compressed checkpoints for inference frameworks.
Swift SDK running open-source speech models (ASR, TTS, VAD, speaker diarization) locally on Apple devices via CoreML and the Neural Engine.
Chinese translation of the Deep Learning textbook by Goodfellow, Bengio, and Courville, with community proofreading.
An end-to-end open source platform for building and deploying machine learning models, with Python and C++ APIs.
Python library providing GPU-accelerated tensor computation like NumPy, plus a tape-based autograd system for building deep neural networks.