lyceum notebook launch provisions a machine, starts a Jupyter notebook server on it, and prints the URL once it’s ready. You connect to the server in your browser and work in JupyterLab as you would locally.
This is the right tool when you want an interactive notebook session on a GPU machine without managing a VM yourself. The session bills for as long as the notebook server is up; stop it from the CLI when you’re done.
For one-shot batch execution of an existing .ipynb file, submit it as a Python run instead — see Launch a Run.
Launching a notebook
| Flag | Default | Description |
|---|---|---|
-m, --machine | cpu | Hardware profile |
-t, --timeout | 600 | Session timeout in seconds (max 600) |
-i, --image | jupyter/base-notebook:latest | Custom Jupyter image |
--token | lyceum | Jupyter notebook token |
-p, --port | 8888 | Port for the Jupyter server |
Listing and stopping
lyceum workloads list like any other execution, with logs and metrics available through the same endpoints.