Prerequisites for a Jupyter Notebook with Cloud GPU

  • VSCode installed
  • Thunder Compute extension installed in VSCode or Cursor
  • Jupyter Notebook extension installed in VSCode or Cursor

Steps to Launch Your Notebook

1. Connect to a Thunder Compute cloud GPU in VSCode

Follow the instructions in our Using Thunder Compute with VSCode guide to set and connect to a remote instance in VSCode.

2. Install the Jupyter extension in your cloud workspace

Open the Extensions panel and install the Jupyter extension inside your Thunder Compute instance.

3. Verify GPU availability inside the notebook

Create a Jupyter Notebook, which is now connected to a Thunder Compute instance with GPU capabilities. To confirm that the GPU is accessible, run the following in a notebook cell:

import torch
print(torch.cuda.is_available())

If everything is set up correctly, the output should be:

True

You now have a Jupyter Notebook running on a Thunder Compute cloud GPU, a fast and low-cost alternative to Colab for indie developers, researchers, and data scientists.