Gradient notebooks are an interactive environment (based on Jupyter Notebook or Jupyter Lab) for developing and running code. You can run Jupyter notebooks, Python scripts and much more, on a GPU, CPU, or even a TPU. A Gradient Notebook = access to a Jupyter Notebook instance. Within that instance you can have limitless notebook documents. You can think of a Gradient Notebook as your persistent, on-demand workspace in the cloud.
Within that instance you can have limitless notebook documents.
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.
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 also add a custom container very easily or build one off of a base template, such as the Jupyter R stack.
There are a number of environment variables loaded into a notebook's environment, which you can access and use. Probably most useful 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 easily, programmatically interact with Gradient.