Quick Start


To begin using Gradient, follow these preliminary steps:

Now you can create Notebooks, Jobs, Projects, Experiments, Models, Deployments, and more!

Note: if you are a Gradient Private Cloud user, please visit the Gradient Private Cloud section for more info on how to utilize private processing site clusters.

Create a Notebook

Notebooks can be created by clicking Create Notebook button on the Notebooks tab. You can stop, start, fork, and swap out the instance type anytime. Choose from a wide selection of pre-configured templates or bring your own. See more info here.

Check out the FREE GPU option when launching Notebooks!

Submit an Experiment

You can run Experiments from the web interface or CLI:

Using the Experiment Builder (Web UI)

Using the CLI

Before creating an experiment using the CLI, you must first install the CLI and create a Project for your Experiments to live in. To create a Project, navigate to Gradient > Projects in the UI and click Create Project. Then select Create Standalone Project and provide a project name. Now, you can use the created Project's Project ID in order to create Experiments in that Project via the CLI.

Example command

The following command will work and will create and start an Experiment that will display properties of the attached GPU. Be sure to replace <your-project-id> with your Project ID.

Note: We recommend stashing your API key with gradient apiKey XXXXXXXXXXXXX or you can add your API key as an option on each Experiment. See Connecting Your Account.

gradient experiments run singlenode --projectId <your-project-id> --container 'Test-Container' --machineType P4000 --command 'nvidia-smi' --name 'test-01' --workspace none --apiKey <your-api-key>

You can also create multi-node and hyperparameter Experiments, and you can use the create command to simply create Experiments that can be started later. Explore all the advanced options here.

Behind the scenes, your Experiment will be uploaded and executed on our cluster of machines starting with the command you provided. There are several optional Experiment parameters, such as to specify your workspace (the additional files to be used in your experiment). You can always use the --help option after any command in the CLI for more info.

Monitor your Experiment progress

Experiments states transition from Queued > Pending > Running. Once the Experiment is in the Running state, you can watch your Experiment run in the CLI and web UI. An Experiment can complete with the following states: Success, Cancelled, Error, or Failed.

Congratulations! You ran your first Experiment on Gradient 🚀

Explore the rest of the platform

From Models to Deployments, there's a lot more to the Gradient platform. We recommend using the Web UI to explore the primary components and also be sure to install the CLI and check out the SDK.