Discover what Lightning Apps can do in 5 min¶
Lightning Apps can be plenty things, and while a picture is worth a thousand words, videos showing you examples should be worth even more.
Flashy - Auto ML App (Public)¶
Train a model on any image or text dataset without writing any code. Flashy uses React.js for its frontend.
Research App (Public)¶
Share your paper
bundled with the arxiv link, poster, live jupyter notebook, interactive demo to try the model, and more!
ScratchPad - Notebook Manager for Team (Public)¶
Run multiple Jupyter Notebooks on cloud CPUs or machines with multiple GPUs.
InVideo Search (Public)¶
This App lets you find anything you’re looking for inside a video. The engine is powered by Open AI CLIP.
AI-powered HackerNews (Public)¶
Save yourself time, and get Hacker News story recommendations, chosen for you specifically. This Lightning App was designed to illustrate a full end-to-end MLOPs workflow aimed at enterprise recommendation systems.
Lightning Apps can turn ML into scalable systems in days — not months¶
Use the Lightning framework to develop any ML system: train and deploy a model, create an ETL pipeline, or spin up a research demo — using the intuitive principles we pioneered with PyTorch Lightning.
Anyone who knows Python can build a Lightning App, even without machine learning experience.
Lightning Apps are:
fault-tolerant, distributed, cost optimized
local and cloud debuggable
highly reactive & interactive
connect multiple UIs together
built for team collaboration
framework agnostic, use your own stack
and much more