how do i run an llm on iphone

Asked on 07/30/2024

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To run a large language model (LLM) on an iPhone, you can follow these steps:

  1. Model Training and Preparation:

    • Start by defining the model architecture and training the model using libraries such as PyTorch or TensorFlow. You can take full advantage of Apple silicon and the unified memory architecture on Mac for this purpose.
    • Once trained, convert the model into the Core ML format using Core ML tools. This step involves optimizing the model representation and parameters to achieve great performance while maintaining good accuracy.
  2. Model Conversion:

    • Use Core ML tools, an open-source Python package, to convert your PyTorch model into the Core ML format. Core ML tools offer various optimization techniques, such as quantization and efficient key-value caching in LLMs, to enhance performance.
  3. Model Integration:

    • Integrate the converted model into your app using the Core ML framework. Core ML optimizes hardware-accelerated execution across the CPU, GPU, and neural engine, ensuring efficient performance on Apple devices.
    • Core ML provides a unified API for performing on-device inference across a wide range of machine learning and AI model types.

For more detailed guidance, you can refer to the following sessions from WWDC 2024:

These sessions cover the entire workflow from training and converting models to integrating and running them on Apple devices.