Gallery is a curated collection of on-device machine learning examples, demo apps, and model artifacts designed to help developers experiment with and deploy ML at the edge. The project bundles runnable samples that show how to run TensorFlow Lite/Edge TPU models (and similar lightweight runtimes) on mobile and embedded platforms, demonstrating common tasks like image classification, object detection, audio recognition, and pose estimation. Each sample is intended to be both a learning aid and a practical starting point: code is organized to show model loading, pre/post-processing, performance measurement, and common optimization knobs (quantization, NNAPI/Delegate usage, and hardware accelerators). The repo also collects small, well-documented models and conversion scripts so developers can reproduce a pipeline from a full-size model down to a device-friendly artifact.
Features
- Experience the magic of GenAI without an internet connection. All processing happens directly on your device
- Easily switch between different models from Hugging Face and compare their performance
- Upload images and ask questions about them. Get descriptions, solve problems, or identify objects
- Transcribe an uploaded or recorded audio clip into text or translate it into another language
- Summarize, rewrite, generate code, or use freeform prompts to explore single-turn LLM use cases
- Engage in multi-turn conversations
Project Samples
