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Run Stable Diffusion on Mac natively. This app uses Apple's Core ML Stable Diffusion implementation to achieve maximum performance and speed on Apple Silicon based Macs while reducing memory requirements. Extremely fast and memory efficient (~150MB with Neural Engine) Runs well on all Apple Silicon Macs by fully utilizing Neural Engine. Generate images locally and completely offline. Generate images based on an existing image (commonly known as Image2Image) Generated images are saved with...

MochiDiffusion is a native macOS application that allows users to run Stable Diffusion models locally, leveraging Apple Silicon GPU acceleration via Core ML. It offers users GUI controls for prompts and model configuration without needing Python or Docker, enabling offline image generation.

This project is a comprehensive, code-first deep learning curriculum built around TensorFlow and Keras, designed to guide learners from foundational concepts to practical model deployment through hands-on experimentation. It is structured as a series of progressively complex Jupyter notebooks that emphasize writing and understanding code before diving into theory, reinforcing learning through repetition and application. The material covers core machine learning workflows including...