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.
Kronos is an open-source decoder-only foundation model pretrained on financial candlestick (K-line) sequences for market forecasting.
A free, MIT-licensed course of 542 lessons on AI engineering, implementing model internals, retrieval, and agent runtimes from scratch.
Inference engine for running AI models locally inside apps, with Rust core and Swift, Python, and TypeScript bindings.
Inference code, checkpoints, and notebooks for Meta's Segment Anything Model (SAM), which produces object masks from points, boxes, or automatically for whole images.
Reference code for Stable Diffusion, a latent text-to-image diffusion model that generates images from text prompts.
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.
Open-source GPU cluster orchestrator and PyTorch-based framework for training LLMs with billions to trillions of parameters.
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.
An end-to-end open source platform for building and deploying machine learning models, with Python and C++ APIs.