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Prerequisites for a Jupyter Notebook with Cloud GPU

  • A supported editor installed: VSCode, Cursor, or Windsurf
  • The Thunder Compute extension installed in that editor
  • The Jupyter extension installed in that editor

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Steps to Launch Your Notebook

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1. Connect to a Thunder Compute cloud GPU in VSCode

Follow the instructions in our quickstart guide to set and connect to a remote instance in VSCode.

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2. Install the Jupyter extension in your cloud workspace

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

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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.