JupyterLab on Spaces
JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data. It is a great tool for data science and machine learning, and it is widely used by the community. With Hugging Face Spaces, you can deploy your own JupyterLab instance and use it for development directly from the Hugging Face website.
⚡️ Deploy a JupyterLab instance on Spaces
You can deploy JupyterLab on Spaces with just a few clicks. First, go to this link or click the button below:
Spaces requires you to define:
An Owner: either your personal account or an organization you’re a part of.
A Space name: the name of the Space within the account you’re creating the Space.
The Visibility: private if you want the Space to be visible only to you or your organization, or public if you want it to be visible to other users.
The Hardware: the hardware you want to use for your JupyterLab instance. This goes from CPUs to H100s.
You can optionally configure a
JUPYTER_TOKENpassword to protect your JupyterLab workspace. When unspecified, defaults tohuggingface. We strongly recommend setting this up if your Space is public or if the Space is in an organization.
Storage in Hugging Face Spaces is ephemeral, and the data you store in the default configuration can be lost in a reboot or reset of the Space. We recommend to save your work to a remote location or to use persistent storage for your data.
Setting up persistent storage
To set up persistent storage on the Space, you go to the Settings page of your Space and choose one of the options: small, medium and large. Once persistent storage is set up, the JupyterLab image gets mounted in /data.
Read more
If you have any feedback or change requests, please don’t hesitate to reach out to the owners on the Feedback Discussion.
Acknowledgments
This template was created by camenduru and nateraw, with contributions from osanseviero and azzr.
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