Podcast
Questions and Answers
What is Core ML?
What is Core ML?
- A machine learning library (correct)
- An image generation tool
- An Apple Silicon device
- A neural network
What is the total number of parameters in the complex pipeline?
What is the total number of parameters in the complex pipeline?
- 100 million
- 1.2 billion
- 1.275 billion (correct)
- 2.5 billion
What is the release comprised of?
What is the release comprised of?
- A Python package and a Swift package (correct)
- A Core ML package and a Swift package
- A Python package and a Core ML package
- A Python package and an Apple Neural Engine
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Study Notes
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Today, we are releasing optimizations to Core ML for Stable Diffusion in macOS 13.1 and iOS 16.2, as well as code to get started with deploying to Apple Silicon devices.
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Core ML is a machine learning library that enables developers to create apps that use image generation from text prompts.
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The community has built an expansive ecosystem of extensions and tools around this core technology in a matter of weeks.
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Getting to a compelling result with Stable Diffusion can require a lot of time and iteration, so a core challenge with on-device deployment of the model is making sure it can generate results fast enough on device.
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This requires executing a complex pipeline comprising 4 different neural networks totaling approximately 1.275 billion parameters.
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To learn more about how we optimized a model of this size and complexity to run on the Apple Neural Engine, you can check out our previous article.
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This release comprises a Python package for converting Stable Diffusion models from PyTorch to Core ML using diffusers and coremltools, as well as a Swift package to deploy the models.
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