LiteRT - Google's High-Performance On-Device AI Runtime
LiteRT, formerly known as TensorFlow Lite, is Google's high-performance runtime for on-device AI, offering optimized, multi-platform support, diverse language compatibility, and high performance.
LiteRT Product Information
What is LiteRT?
LiteRT (formerly TensorFlow Lite) is Google's high-performance runtime for on-device AI. It addresses essential on-device machine learning (ODML) constraints, provides multi-platform support, facilitates the use of diverse language support, and ensures high performance through specialized delegates such as GPU and iOS Core ML.
How to Use LiteRT?
LiteRT enables you to identify suitable ML problems, choose or convert models, and integrate them into your apps with SDKs for Java/Kotlin, Swift, Objective-C, C++, and Python. The workflow includes identifying ML problems, choosing models, and implementing them on-device with flexible and customizable options.
Core Features of LiteRT
- Optimized runtime for on-device AI
- Support for multi-platform and multi-framework models
- Diverse language support with SDKs
- High performance through specialized delegates
- Model conversion and optimization tools
Use Cases of LiteRT
- On-device machine learning tasks
- Flexible and customizable model implementation
- Integration into Java, Kotlin, Swift, Objective-C, C++, and Python apps
- High-performance inference with specialized delegates
FAQ about LiteRT
What is LiteRT?
LiteRT, formerly known as TensorFlow Lite, is Google's high-performance runtime for on-device AI, offering optimized, multi-platform support, diverse language compatibility, and high performance.
What constraints does LiteRT address for on-device machine learning?
LiteRT addresses five essential on-device machine learning (ODML) constraints: latency, privacy, connectivity, size, and power consumption.
What model options does LiteRT provide?
LiteRT includes tools to convert models from TensorFlow, PyTorch, and JAX into the FlatBuffers format, offering a wide range of frameworks for on-device AI implementation.
What language support does LiteRT offer?
LiteRT provides SDKs for Java/Kotlin, Swift, Objective-C, C++, and Python, ensuring diverse language compatibility for on-device AI applications.
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