How come you always have to install some version of pytorch or tensor flow to run these ml models? When I'm only doing inference shouldn't there be easier ways of doing that, with automatic hardware selection etc. Why aren't models distributed in a standard format like onnx, and inference on different platforms solved once per platform?

The repo is aimed at developers and has two parts. The first adapts the ML model to run on Apple Silicon (CPU, GPU, Neural Engine), and the second allows you to easily add Stable Diffusion functionality to your own app.

If you just want an end user app, those already exist, but now it will be easier to make ones that take advantage of Apple's dedicated ML hardware as well as the CPU and GPU.

>This repository comprises:

    python_coreml_stable_diffusion, a Python package for converting PyTorch models to Core ML format and performing image generation with Hugging Face diffusers in Python

    StableDiffusion, a Swift package that developers can add to their Xcode projects as a dependency to deploy image generation capabilities in their apps. The Swift package relies on the Core ML model files generated by python_coreml_stable_diffusion