# EdgeTPU: Machine Learning Models Optimized for Google Tensor ## Requirements [![TensorFlow 2.4](https://img.shields.io/badge/TensorFlow-2.4-FF6F00?logo=tensorflow)](https://github.com/tensorflow/tensorflow/releases/tag/v2.4.0) [![Python 3.7](https://img.shields.io/badge/Python-3.7-3776AB)](https://www.python.org/downloads/release/python-379/) ## Overview
An illustration of NAS to find Edge TPU optimized models
This repository contains machine learning models optimized for Edge TPU in Pixel 6's SoC, [Google Tensor](https://blog.google/products/pixel/google-tensor-debuts-new-pixel-6-fall/). We use Neural Architecture Search (NAS) to automate the process of designing ML models and incentivize the search algorithms to discover models that achieve higher quality as well as better latency and computing efficiency. This automation also allows us to scale the development of ML models for a variety of on-device tasks. We’re making these ML models publicly available through the Tensorflow model garden and [Tensorflow Hub](https://tfhub.dev/s?q=edgetpu) to enable researchers and developers to bootstrap further use case development on Pixel 6. ### [Image Classification](https://github.com/tensorflow/models/tree/master/official/projects/edgetpu/vision#edgetpu-optimized-vision-models) ### [Object Detection](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf1_detection_zoo.md#pixel-6-edge-tpu-models) ### [Semantic Segmentation](https://github.com/tensorflow/models/tree/master/official/projects/edgetpu/vision#edgetpu-optimized-vision-models) ### [Natural Language Understanding](https://github.com/tensorflow/models/tree/master/official/projects/edgetpu/nlp#mobilebert-edgetpu)