Run Jupyter Notebooks
Set up and run Jupyter Notebooks on Thunder Compute’s affordable cloud GPUs. Connect via VSCode, install extensions, and verify GPU access for ML/data science.
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:
If everything is set up correctly, the output should be:
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.