After it’s been trained, the projection model can be used directly for inference on device. In future releases, TensorFlow Lite will support more models and built-in operators, performance ...

a new FlatBuffers-based model file format, an on-device interpreter with kernels, the TensorFlow converter, and pre-tested models. In addition, TensorFlow Lite supports the Android Neural Networks ...

The basic idea of TensorFlow Lite is that you train a full-blown TensorFlow model and convert it to the TensorFlow Lite model format. Then you can use the converted file in your mobile application ...

In TensorFlow Lite, these files are called “TensorFlow Lite Model Files” and have the ... graph using the TOCO (Tensor Flow Optimizing Converter Tool). This gives us a nice “pre-trained ...

The TensorFlow Lite team at Google also shared its roadmap ... the API to make it generally available A TensorFlow 2.0 model converter to make Lite models will be made available for developers ...

Learn more Google today announced TensorFlow Lite Model Maker, a tool that adapts state-of-the-art machine learning models to custom data sets using a technique known as transfer learning.

With TensorFlow Lite, the same models can target mobile phones, IoT devices, and edge computing environments. This makes it possible to train the model once and deploy it to an Android phone ...