awesome-tensorflow-lite
github.com/margaretmz/awesome-tensorflow-lite ↗An awesome list of TensorFlow Lite models, samples, tutorials, tools and learning resources.
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Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
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Installation instructions →What's inside
Helpful links
- Adventures in TensorFlow Lite
A repository showing non-trivial conversion processes and general explorations in TensorFlow Lite.
- AI benchmark
A website for benchmarking computer vision models on smartphones.
- Material design guidelines for ML
How to design machine learning powered features. A good example:
- Netron
A tool for visualizing models.
- Performance measurement
How to measure model performance on Android and iOS.
- TensorFlow Lite Examples - Android
A repository refactors and rewrites all the TensorFlow Lite Android examples which are included in the TensorFlow official website.
Learning resources
- AI and Machine Learning for CodersBooks
By Laurence Moroney (
- AI and Machine Learning On-Device DevelopmentBooks
By Laurence Moroney (
- Android ML by Hoi LamVideos
- Complete BundleBooks
TOC) - By the PyImageSearch Team: Adrian Rosebrock (@PyImageSearch), David Hoffman, Asbhishek Thanki, Sayak Paul (@RisingSayak), and David Mcduffee.
- Contributing to TensorFlow Lite with Sunit RoyVideos
- Device-based Models with TensorFlow LiteMOOCs
Coursera course by Laurence Moroney (
Past announcements:
- Android Support Library
Makes mobile development easier (
- Announcement of the new converter
- Hexagon delegate
How to use the Hexagon Delegate to speed up model inference on mobile and edge devices. Also see blog post
- Model Maker
Create your custom
- Model Metadata
Provides a standard for model descriptions which also enables
- On-device training
It is finally here! Currently limited to transfer learning for image classification only but it's a great start. See the official
ML Kit examples
- Building a Custom Machine Learning Model on Android with TensorFlow Lite
- Computer Vision with ML Kit - Flutter In Focus
Flutter In Focus
- Flutter + MLKit: Business Card Mail Extractor
A blog post with a
- From TensorFlow to ML Kit: Power your Android application with machine learning
A talk with
- ML Kit and Face Detection in Flutter
- ML Kit on Android 1: Intro
Plugins and SDKs
- Coral Edge TPU
Edge hardware by Google.
- Edge Impulse
Created by
- MediaPipe
A cross platform (mobile, desktop and Edge TPUs) AI pipeline by Google AI. (PM
- MediaPipeMing Yong
MediaPipe examples.
- TensorFlow Lite Flutter Plugin
Provides a dart API similar to the TensorFlow Lite Java API for accessing TensorFlow Lite interpreter and performing inference in flutter apps.
Ideas and Inspiration
- E2E TFLite Tutorials
Checkout this repo for sample app ideas and seeking help for your tutorial projects. Once a project gets completed, the links of the TensorFlow Lite model(s), sample code and tutorial will be added to this awesome list.
Model zoo
- MobileNetTensorFlow Lite models
Pretrained MobileNet v2 and v3 models.
- Pretrained modelsTensorFlow Lite models
Quantized and floating point variants.
- Tensorflow detection model zooTensorFlow models
Pre-trained on COCO, KITTI, AVA v2.1, iNaturalist Species datasets.
- TensorFlow HubTensorFlow Lite models
Set "Model format = TFLite" to find TensorFlow Lite models.
- TensorFlow Lite modelsTensorFlow Lite models
With official Android and iOS examples.
- TensorFlow modelsTensorFlow models
Official TensorFlow models.
Showing a sample of 69 resources. View the full list on GitHub →