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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.

Smart reply

Generate reply suggestions to input conversational chat messages.

Community participation

See more ways to participate in the TensorFlow community.

TensorFlow Lite on GitHub 
Ask a question on StackOverflow 
Community discussion forum 
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News & announcements
June 11, 2019 
TensorFlow Integer Quantization

Integer quantization is a new addition to the TensorFlow Model Optimization Toolkit. It is a general technique that reduces the numerical precision of the weights and activations of models to reduce memory and improve latency.

May 14, 2019 
TensorFlow Pruning API

Weight pruning, a new addition to the TensorFlow Model Optimization toolkit, aims to reduce the number of parameters and operations involved in the computation by removing connections, and thus parameters, in between neural network layers.

May 8, 2019 
TensorFlow Lite at Google I/O'19

In this video, you'll learn how to build AI into any device using TensorFlow Lite, and learn about the future of on-device ML and our roadmap. You’ll also discover a library of pretrained models that are ready to use in your apps or to be customized for your needs.

Jan 16, 2019 
TensorFlow Lite Now Faster with Mobile GPUs (Developer Preview)

Run inference on GPU can improve inference up to ~4x on Pixel 3.