Notebooks How-Tos

Generated on 5 May 2025

Notebooks are a web-based Jupyter IDE with shared persistent storage for long-term development and inter-notebook collaboration, backed by accelerated compute.

Getting Started

How to Create Notebooks

Create a notebook using Paperspace’s CPU- and GPU-backed machines.

How to Swap Machines Attached to Notebooks

Swap and see the kernel state for machines attached to notebooks.

How to Fork Notebooks

Fork a notebook to create a clone of a public notebook into your workspace or to duplicate a notebook already in your workspace.

Collaboration

How to Share Notebooks

Share access to Notebooks to let other users view and run your notebook.

How to Add a Run on Gradient Badge for Notebooks

Use a Run on Gradient URL or badge to share Gradient Notebooks on Paperspace.

Manage Data

How to Create Datasets for Notebooks

Create datasets using the Paperspace console and command line.

How to Mount Datasets in a Gradient Notebook

Mount existing team datasets, public datasets, and create new team datasets to explore data and training models.

How to Upload and Download Datasets and Files from Gradient Notebooks

Upload and download files from the file manager, transfer files from Google Drive to your notebook, and access shared persistent storage.

How to Connect S3-Compatible Data Sources to Notebooks

Mount public or private S3 buckets into notebooks to access data stored externally.

Manage Storage

How to Set Up Storage Providers for Notebooks

Add DigitalOcean Spaces Object Storage or another public storage provider.

How to Manage Storage for Notebooks

Manage storage in Linux-based environment.

Configuration

How to Use the Terminal to Access Notebook Machines

Access a terminal in Gradient Notebooks to use root access to the underlying machine.

How to Connect to Remote Jupyter Kernel

Connect to remote Jupyter kernels through alternative IDEs.

How to Access and Restart Jupyter Kernels

How to check on Jupyter kernel states

Manage Containers

Manage containers to ensure reproducible results when using Notebooks, Workflows, and Deployments.

Logs and Metrics

How to View Logs for Gradient Notebooks

Access real time and post-workload system logs for Gradient Deployments.

How to View Metrics For Gradient Notebooks

Access CPU usage, RAM usage, and GPU performance metrics for Gradient Notebooks.

How to Use TensorBoard in Notebooks

Use TensorBoard, a visualization toolkit from TensorFlow, within Gradient notebooks to visualize metrics and histograms, display images, and more.

We can't find any results for your search.

Try using different keywords or simplifying your search terms.