Deploy machine learning models on mobile and IoT devices
TensorFlow Lite is an open source deep learning framework for on-device inference.
How it works
Pick a model
Pick a new model or retrain an existing one.
Convert a TensorFlow model into a compressed flat buffer with the TensorFlow Lite Converter.
Take the compressed .tflite file and load it into a mobile or embedded device.
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.
News & announcements
See updates to help you with your work, and subscribe to our monthly TensorFlow newsletter to get the latest announcements sent directly to your inbox.
Try out a new on-device transfer learning image classification example.
Post-training float16 quantization reduces TensorFlow Lite model sizes up to 50% while sacrificing very little accuracy - and is great for GPUs!