# Workflows How-Tos (private)

Generated on 20 Mar 2026

Workflows automate machine learning tasks, combining GPU instances with an expressive syntax to generate production-ready machine learning pipelines with a few lines of code.

## Getting Started

[How to Manage Workflows with the Paperspace GUI and CLI](https://docs.digitalocean.com/products/paperspace/workflows/how-to/manage-workflows/index.html.md): Use the Paperspace GUI and CLI to create new Workflows, import existing ones, and run them.

[How to Create Datasets for Gradient Workflows](https://docs.digitalocean.com/products/paperspace/workflows/how-to/create-datasets/index.html.md): Create a new dataset for Workflows in the command line or UI.

## Configuration

[How to Use Custom Containers in Gradient Workflows](https://docs.digitalocean.com/products/paperspace/workflows/how-to/manage-containers/index.html.md): Use and manage custom containers in Gradient Workflows to define reproducible environments for each Workflow step.

[How to Connect to the Gradient GitHub App](https://docs.digitalocean.com/products/paperspace/workflows/how-to/connect-to-github-app/index.html.md): The Gradient GitHub App lets you start training runs in Workflows and Deployments by listening for commits in GitHub.

[How to Use the Gradient Model Repository to Manage Models](https://docs.digitalocean.com/products/paperspace/workflows/how-to/use-model-repo/index.html.md): Use the Gradient Model repository to import, manage, and deploy ML models.