在行動裝置和 IoT 裝置上部署機器學習模型
TensorFlow Lite 是一種開放原始碼深度學習架構，可在裝置端執行推論。
我們的幾位 TensorFlow Lite 使用者
Learn about TensorFlow Lite’s end-to-end support for NLP tasks with new features including pre-trained NLP models, model creation, conversion and deployment on edge devices.
We are excited to open source an end-to-end solution for TFLite on-device recommendation tasks. We invite developers to build on-device models using our solution that provides personalized, low-latency and high-quality recommendations, while preserving users’ privacy.
A set of powerful and easy-to-use task-specific APIs for app developers to create ML experiences with TensorFlow Lite. The TensorFlow Lite Task Library currently supports six ML tasks including Vision and NLP use cases.
An end-to-end tutorial on how to convert a TF 1.x model to TensorFlow Lite (TFLite) and deploy it to an Android app. We use Android Studio’s ML Model Binding to import the model for cartoonizing an image captured with CameraX.