Deploy machine learning models on mobile and IoT devices

TensorFlow Lite is an open source deep learning framework for on-device inference.

See the guide

Guides explain the concepts and components of TensorFlow Lite.

See examples

Explore TensorFlow Lite Android and iOS apps.

See models

Easily deploy pre-trained models.

How it works

Pick a model

Pick a new model or retrain an existing one.

Convert

Convert a TensorFlow model into a compressed flat buffer with the TensorFlow Lite Converter.

Deploy

Take the compressed .tflite file and load it into a mobile or embedded device.

Optimize

Quantize by converting 32-bit floats to more efficient 8-bit integers or run on GPU.

Solutions to common problems

Explore optimized models to help with common mobile and edge use cases.

Image classification

Identify hundreds of objects, including people, activities, animals, plants, and places.

Object detection

Detect multiple objects with bounding boxes. Yes, dogs and cats too.

Question answering

Use a state-of-the-art natural language model to answer questions based on the content of a given passage of text with BERT.

News & announcements

Check out our blog for additional updates, and subscribe to our monthly TensorFlow newsletter to get the latest announcements sent directly to your inbox.

December 18, 2020  
How to generate super resolution images using TensorFlow Lite on Android

The task of recovering a high resolution (HR) image from its low resolution counterpart is commonly referred to as Single Image Super Resolution (SISR). In this tutorial, we use a pre-trained ESRGAN model from TensorFlow Hub and generate super resolution images using...

December 2, 2020  
Build sound classification models for mobile apps with Teachable Machine and TFLite

We are excited to announce that Teachable Machine now allows you to train your own sound classification model and export it in the TensorFlow Lite (TFLite) format. Then you can integrate the TFLite model to your mobile applications or your IoT devices. This is an easy...

November 25, 2020  
Training and deploying ML models on edge devices (TF Fall 2020 Updates)

Learn how to train and deploy an ML model on an Android app in just a few lines of code with TensorFlow Lite Model Maker and Android Studio. From here you can then explore how to use various tools from Google to turn a prototype into a production app. Presented by...

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November 23, 2020  
Intro to On-device Machine Learning (TF Fall 2020 Updates)

Learn about the differences between ML on a supercomputer and ML on a portable device, and the tools and technologies that Google has developed to allow you to bring your work to mobile devices without reinventing the wheel. We'll cover the basics and also special...

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