PyTorch Live is a set of tools to build AI-powered experiences for mobile.

This monorepo includes the PyTorch Live command line interface (i.e., torchlive-cli), a React Native package to run on-device inference with PyTorch Mobile, and a React Native template with examples ready to be deployed on mobile devices.

• Requirements
• Building your first PyTorch Live app
• How to Contribute
• Code of Conduct
• License

PyTorch Live apps may target Android 10.0 (API 29) and iOS 12.0 or newer. You may use Windows, macOS, or Linux as your development operating system, though building and running the PyTorch Live CLI is limited to macOS.

Follow the Getting Started guide. PyTorch Live offers a CLI with convenient commands to install development dependencies and initialize new projects. We also have a few tutorials for you to keep going after getting started:

• Image Classification
• Question Answering
• Prepare Custom Model

The full documentation for PyTorch Live can be found on our website.

The main purpose of this repository is to continue evolving PyTorch Live. We want to make contributing to this project as easy and transparent as possible, and we are grateful to the community for contributing bug fixes and improvements. Read below to learn how you can take part in improving PyTorch Live.

Facebook has adopted a Code of Conduct that we expect project participants to adhere to. Please read the full text so that you can understand what actions will and will not be tolerated.

Read our Contributing Guide to learn about our development process, how to propose bugfixes and improvements, and how to build and test your changes to PyTorch Live.

PyTorch Live is MIT licensed, as found in the LICENSE file.