Quick Start - Jupyter Notebook

Follow this guide to learn how to spin up a Jupyter Notebook on FloydHub's deep-learning servers.

Quick Preparation Checklist

Quick Start

  1. Visit https://www.floydhub.com/projects/create and create a FloydHub project: create jupyter notebook

  2. In your terminal, use Floyd CLI to initialize the project (be sure to use the name you gave the project in step one):

    $ floyd init my_jupyter_project
    Project "my_jupyter_project" initialized in current directory
  3. Then, kick off your first Jupyter Notebook with floyd run --gpu --mode jupyter

    $ floyd run --mode jupyter
    Creating project run. Total upload size: 198.0B
    Syncing code ...
    [================================] 946/946 - 00:00:00
    Setting up your instance and waiting for Jupyter notebook to become available .............
    Path to jupyter notebook: https://floydlabs.com/notebooks/gaftzXTdaPtQtQ9NvEieNg

    This will open up a Jupyter Notebook in your browser. The notebook is running on FloyHub's GPU servers. Just like that, you're up and running!

Congratulations! You've just started your first Jupyter Notebook on FloydHub 🎉

To go a bit more in-depth and learn more about using Jupyter Notebooks on FloydHub, check out the Getting Started Tutorial - Jupyter Notebook or you can watch this 3-minute Lightning Video on running Jupyter Notebooks on FloydHub:

Stopping your Notebook

On the project page, click the Cancel button below the icon that shows the status of your job, as shown in the picture below:

Stop Job

Then click the Confirm button in the modal that pops up: Stop Job Confirm


Jupyter Notebooks are designed for interactive development. Your job starts running on FloydHub's server when you execute the floyd run --mode jupyter command and it continues to be active till you explicitly stop your job.

Hence, even if you are not actively executing code inside your Notebook, the Jupyter server is still active on FloydHub and you are billed for the time.

Video Tutorial

Help make this document better

This guide, as well as the rest of our docs, are open-source and available on GitHub. We welcome your contributions.