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Generated on 8/7/2024

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It seems like your question is off-topic. However, I can provide information about the content presented by Apple at WWDC related to machine learning and AI models. Here are some relevant sessions and their chapters:

  1. Train your machine learning and AI models on Apple GPUs

    • Introduction
    • Training frameworks on Apple silicon
    • PyTorch improvements
    • ExecuTorch
    • JAX features

  2. Accelerate machine learning with Metal

    • Introduction
    • Transformer support
    • Fast Fourier transforms
    • MPS Graph viewer

  3. Bring your machine learning and AI models to Apple silicon

    • Introduction
    • Model compression
    • Stateful model
    • Transformer optimization
    • Multifunction model

If you have any specific questions about these sessions or topics, feel free to ask!

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Accelerate machine learning with Metal

Accelerate machine learning with Metal

Learn how to accelerate your machine learning transformer models with new features in Metal Performance Shaders Graph. We’ll also cover how to improve your model’s compute bandwidth and quality, and visualize it in the all new MPSGraph viewer.

Bring your machine learning and AI models to Apple silicon

Bring your machine learning and AI models to Apple silicon

Learn how to optimize your machine learning and AI models to leverage the power of Apple silicon. Review model conversion workflows to prepare your models for on-device deployment. Understand model compression techniques that are compatible with Apple silicon, and at what stages in your model deployment workflow you can apply them. We’ll also explore the tradeoffs between storage size, latency, power usage and accuracy.

Train your machine learning and AI models on Apple GPUs

Train your machine learning and AI models on Apple GPUs

Learn how to train your models on Apple Silicon with Metal for PyTorch, JAX and TensorFlow. Take advantage of new attention operations and quantization support for improved transformer model performance on your devices.