The Runtime Formerly Known as TensorFlow Lite

LiteRT is the  Google on-device runtime for machine learning, formerly known as TensorFlow Lite. 

You can convert TensorFlow, PyTorch and JAX models to the TFLite format. 

This can be done using AI Edge conversion tools.

LiteRT rises to various ODML (On-Device Machine Learning) challenges:

1. Connectivity - ability to execute without an Internet connection

2. Size - reduced model and binary size

3. Privacy/data restrictions - no personal data leaves the device

4. Power consumption - efficient inference and a lack of network connections

Operationally, LiteRT models use an efficient portable format known as FlatBuffers, and the .tflite file extension. (See here for the difference between FlatBuffers and protobuf).