Overview

This section of the documentation covers our previous generation of Gradient. For the current version go to Gradient Next.

What is a Notebook?

Gradient notebooks are an interactive environment (based on Jupyter Notebook or Jupyter Lab) for developing and running code. You can run Jupyter notebooks on a GPU, CPU, or even a TPU.

A Gradient **Notebook gives you access to a full Jupyter Notebook environment. Within the Notebook, you can store an unlimited number of documents and other files. You can think of a Gradient Notebook as your persistent, on-demand workspace in the cloud.

NEW! Visit the new ML Showcase for a list of sample projects you can fork into your own account.

File Storage

Any data stored in /storage will be preserved for you across restarts. Persistent storage is backed by a filesystem and is ideal for storing data like images, datasets, model checkpoints etc. Learn more about persistent storage here.

Containers

Because everything is running in a Docker container behind the scenes, we support any kernel you would like. We have a handful of pre-built containers and you can easily add a custom container or build one from a base template, such as the Jupyter R stack.

View the list of pre-built containers here.

Environment Variables

There are a number of environment variables loaded into a notebook's environment, which you can access and use. Probably most common is is PS_API_KEY , which will contain your most recently created API key (if you've created one). In combination with the Gradient SDK, this allows you to programmatically interact with Gradient.