> For the complete documentation index, see [llms.txt](https://docs.robbie.run/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.robbie.run/running-your-experiments-on-robbie/jupyter-notebooks.md). # Jupyter Notebooks Jupyter Notebooks are open-source documents that can be used to create, prototype, and share computational documents. They can be used for various purposes, including data science, scientific computing, computational journalism, and machine learning. One of the biggest challenges of using Jupyter Notebooks for machine learning is related to the use of GPUs (needed to speed up machine learning computations). Unfortunately, Jupyter Notebooks reserve and hold a GPU the entire time the notebook is open, even when idle and not running Python code. Furthermore, machine learning experiments often comprise other distinct phases, such as data preparation and visualization, that do not require a GPU. These shortcomings prevent others from using the GPU, drive up GPU costs, and force administrators to restrict GPU access. Robbie solves this problem by enabling users to access high-performance GPUs in a Jupyter Notebook, whether hosted on a local machine, a non-GPU notebook server, or Google Colab. There are three ways to access GPUs via Robbie in your Jupyter Notebook: * Robbie Remote Function * Robbie Magic * Robbie Notebook Runner --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.robbie.run/running-your-experiments-on-robbie/jupyter-notebooks.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.