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.
Inference engine for running AI models locally inside apps, with Rust core and Swift, Python, and TypeScript bindings.
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.