Using GIT from inside a Jupyter Notebook ML Container - What NVidia AI Workbench needs...

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  • Опубликовано: 22 июн 2024
  • Jupyter Notebooks provide a browser-based experience that provides an integrated development environment in your local browser no matter where the work is being done.
    The AI Workbench lets you experiment, train, and run ML workloads in remote containers. This is an awesome way to support encapsulation and remote execution.
    Version control and GIT integration are the missing links when you are sitting on a different machine or in a different environment from the one where the Jupyter Notebook container is running. You can use the AI Workbench GIT UI or a GIT CLI via SSH. A third option is to load Jupyter and Python jupyterlab-cli. This Python module acts as a Jupyter Notebook extension that lets you manage your GIT repository from inside the notebook environment.
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