apple/coremltools

Health v2 · maintenance only

Adoption not part of the score

5436 stars · 858 forks observed · 2026-10-07

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Apple's official Python package for converting machine learning models from TensorFlow, PyTorch, scikit-learn, XGBoost, and LibSVM into the Core ML format. It also supports reading, editing, optimizing, and validating Core ML models for on-device deployment in Apple apps.

Use cases

• convert a pytorch model to core ml format
• deploy a trained tensorflow model on iphone
• optimize a core ml model for the neural engine
• convert a scikit-learn model for ios app integration
• edit and validate an existing core ml model
• run on-device inference with core ml in an xcode app

When to choose

• you need to ship trained models to iOS, macOS, watchOS, or visionOS apps via Core ML
• you want Apple-supported conversion from PyTorch or TensorFlow with Neural Engine optimization
• you need to inspect, edit, or compress Core ML model weights

When to avoid

• you target Android, Windows, or Linux on-device inference rather than Apple platforms
• you need a general model exchange format like ONNX instead of Core ML
• your workflow is training-only with no Apple deployment

Facets

library · maturity active

machine-learning sdk developer-tools machine-learning apple-ecosystem deep-learning python cross-platform coreml model-conversion model-optimization tensorflow pytorch on-device-inference apple macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="apple/coremltools")