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Install dependencies
After you create a user-managed notebooks instance, you might need to
install software that
your notebook depends on. You can install dependencies by adding install
commands to a file in your notebook or by using a terminal
window.
An advantage of adding install commands to a file is that, when you share
a notebook, the commands to install the dependencies are saved with the
notebook and are available to users that you share the notebook with.
Install dependencies from a user-managed notebooks instance
To install Python packages from a user-managed notebooks
instance:
In the Google Cloud console, go to the User-managed notebooks page.
Select the instance where you want to install dependencies.
Click Open JupyterLab.
To open a terminal window, you can use the menu or the Launcher.
Menu
To open a terminal window from the menu, select
File > New > Terminal.
The terminal window opens.
Launcher
To open a terminal window from the Launcher, select
File > New > Launcher.
In Other, click the Terminal tile.
The terminal window opens.
In the terminal window, enter the command to install the software
dependency for your user-managed notebooks instance.
To install the mxnet
deep learning library for Python 3 notebooks, enter the following
command:
pip3 install mxnet
When installation is complete, restart the kernel to make sure the
library is available for import. In every open notebook file in the
same user-managed notebooks instance, select
Kernel > Restart kernel.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-29 UTC."],[],[],null,["# Install dependencies on a Vertex AI Workbench user-managed notebooks instance\n\nInstall dependencies\n====================\n\n\n| Vertex AI Workbench user-managed notebooks is\n| [deprecated](/vertex-ai/docs/deprecations). On\n| April 14, 2025, support for\n| user-managed notebooks will end and the ability to create user-managed notebooks instances\n| will be removed. Existing instances will continue to function\n| but patches, updates, and upgrades won't be available. To continue using\n| Vertex AI Workbench, we recommend that you\n| [migrate\n| your user-managed notebooks instances to Vertex AI Workbench instances](/vertex-ai/docs/workbench/user-managed/migrate-to-instances).\n\n\u003cbr /\u003e\n\nAfter you create a user-managed notebooks instance, you might need to\ninstall software that\nyour notebook depends on. You can install dependencies by adding install\ncommands to a file in your notebook or by using a terminal\nwindow.\n\nAn advantage of adding install commands to a file is that, when you share\na notebook, the commands to install the dependencies are saved with the\nnotebook and are available to users that you share the notebook with.\n\nInstall dependencies from a user-managed notebooks instance\n-----------------------------------------------------------\n\nTo install Python packages from a user-managed notebooks\ninstance:\n\n1. In the Google Cloud console, go to the **User-managed notebooks** page.\n\n [Go to User-managed notebooks](https://console.cloud.google.com/vertex-ai/workbench/user-managed)\n2. Select the instance where you want to install dependencies.\n\n3. Click **Open JupyterLab**.\n\n4. To add a notebook file, you can use the menu or the Launcher.\n\n ### Menu\n\n 1. To add a new notebook file from the menu, select\n **File \\\u003e New \\\u003e Notebook**.\n\n 2. In the **Select kernel** dialog, select the kernel for your new\n notebook, for example, **Python 3** , and then click **Select**.\n\n Your new notebook file opens.\n\n ### Launcher\n\n 1. To add a new Python 3 notebook file from the Launcher, select\n **File \\\u003e New \\\u003e Launcher**.\n\n 2. Click the **Python 3** tile.\n\n Your new notebook file opens.\n5. Rename your new notebook file.\n\n ### Menu\n\n 1. Select **File \\\u003e Rename notebook** . The\n **Rename file** dialog opens.\n\n 2. In the **New name** field, change `Untitled.ipynb` to something\n meaningful, such as `install.ipynb`.\n\n 3. Click **Rename**.\n\n ### Launcher\n\n 1. Right-click the `Untitled.ipynb` tab and then click\n **Rename notebook** . The **Rename file** dialog opens.\n\n 2. In the **New name** field, change `Untitled.ipynb` to something\n meaningful, such as `install.ipynb`.\n\n 3. Click **Rename**.\n\n6. Install dependencies as follows.\n\n When you open your new notebook, there is a default code cell where you\n can enter code, in this case Python 3.\n\n To install the [mxnet](https://mxnet.apache.org/)\n deep learning library in a Python 3 notebook, enter the following\n command in the code cell:\n\n `%pip install mxnet`\n\n7. Click the run button to run the install command.\n\n8. When installation is complete, select\n **Kernel \\\u003e Restart kernel**\n to restart the kernel and ensure the library is available for import.\n\n9. Select **File \\\u003e Save notebook** to save the notebook.\n\nInstall dependencies from a terminal\n------------------------------------\n\nTo connect to a terminal, you can use your JupyterLab notebook or\n[SSH](/vertex-ai/docs/workbench/user-managed/ssh-access). To install Python\npackages from a terminal:\n\n1. In the Google Cloud console, go to the **User-managed notebooks** page.\n\n [Go to User-managed notebooks](https://console.cloud.google.com/vertex-ai/workbench/user-managed)\n2. Select the instance where you want to install dependencies.\n\n3. Click **Open JupyterLab**.\n\n4. To open a terminal window, you can use the menu or the Launcher.\n\n ### Menu\n\n To open a terminal window from the menu, select\n **File \\\u003e New \\\u003e Terminal**.\n\n The terminal window opens.\n\n ### Launcher\n\n 1. To open a terminal window from the Launcher, select\n **File \\\u003e New \\\u003e Launcher**.\n\n 2. In **Other** , click the **Terminal** tile.\n\n The terminal window opens.\n5. In the terminal window, enter the command to install the software\n dependency for your user-managed notebooks instance.\n\n To install the [mxnet](https://mxnet.apache.org/)\n deep learning library for Python 3 notebooks, enter the following\n command:\n\n `pip3 install mxnet`\n\n6. When installation is complete, restart the kernel to make sure the\n library is available for import. In every open notebook file in the\n same user-managed notebooks instance, select\n **Kernel \\\u003e Restart kernel**.\n\n7. Select **File \\\u003e Save notebook** to save the notebook."]]