![]() ![]() Add Kite’s largest ML models to a GPU-powered server for smarter, longer completions.Deploy Kite on your JupyterHub server to instantly bring AI-powered completions and one-click documentation to the whole team.JupyterHub: Boost the whole team’s productivity with Kiteĭoes your team use JupyterHub? We offer additional features for JupyterHub teams: If you have never used a module or function before, you can get documentation faster with the Kite Copilot. ![]() If you’re having trouble remembering a calculation or code pattern, Kite can remind you so you don’t need to search on Google.If you already know what you need to type, Kite helps you jump ahead to the next task.This means Kite can predict relevant chunks of code and put them in your completions. Kite’s deep learning models have learned the most popular patterns used by data scientists, plus they understand the context of your code. With how fast data science tooling evolves, it’s critical to stay on top of new modules and APIs, and Kite’s completions help make that easier to do. We’ve trained Kite’s deep learning models on over 25 million open-source Python files to ensure Kite works with your favorite libraries. Kite makes coding with Python faster and more enjoyable Follow the instructions here to install the JupyterLab plugin. Kite for JupyterLab comes in a Free and a Pro version (free 30-day trial), and works 100% locally. We’re tracking this issue in our public Github repo here and here. Unfortunately these editors provide proprietary notebook support which prevents us from building compatibility for the time being. 2 Kite also works in other editors, like P圜harm and VS Code. Plus, no code is sent to a cloud server for processing. ![]() This means if your kernel’s busy reading in data, you‘ll still get Kite completions while coding in other cells.
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