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Core ML FormatGithub
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Overview

  • Introduction
  • Installation
  • Quickstart Example
  • Migrating to This Version
  • Contributing
    • GitHub
    • Contribution Guidelines
  • Release Notes

Neural Networks

  • Unified Conversion API
  • TensorFlow 1 Conversion
    • Convert a TensorFlow 1 Image Classifier
    • Convert a TensorFlow 1 DeepSpeech Model
  • TensorFlow 2 Conversion
    • Convert TensorFlow 2 BERT Transformer Models
  • PyTorch Conversion
    • Model Tracing
    • Model Scripting
    • Convert a PyTorch Segmentation Model
  • Model Intermediate Language
  • Conversion Options
    • Image Inputs
    • Classifiers
    • Flexible Input Shapes
    • Composite Operators
    • Custom Operators
  • Quantization
  • Other Converters
    • Multi-backend Keras
    • ONNX
    • Caffe

Trees & Linear Models

  • LibSVM
  • Scikit-learn
  • XGBoost

MLModel

  • MLModel Overview
  • Model Prediction
  • Xcode Model Preview Types
  • MLModel Utilities

Updatable Models

  • Updatable Models Overview
  • Nearest Neighbor Classifier
  • Neural Network Classifier
  • Pipeline Classifier

Other Converters

Suggest Edits

In addition to PyTorch and TensorFlow, you can also convert neural networks saved in the following formats to Core ML:

  • Multi-backend Keras
  • ONNX
  • Caffe

🚧

Maintenance mode only

The utilities to convert models from these packages to Core ML are in maintenance mode, and will receive only bug fixes. No additional features will be added.

Updated over 4 years ago