Dependencies
Notebooks in the JupyterLab application include PyTorch by default. To install more Python dependencies in a notebook, run!pip install <package_name> ... in a notebook cell:
apt install because they require sudo, and the application does not provide a password.
Working with files
You can upload files to your JupyterLab notebooks and download files and notebooks themselves. The recommended method of uploading files depends on the file size.Uploading smaller files in the file browser
If your files are smaller than 3 , you can upload them directly in the JupyterLab file browser. To open the file browser in your notebook, click
in the left sidebar. To upload files, drag and drop them onto the file browser or click 
Upload.
For more details, see the JupyterLab documentation.
Uploading larger files (3 GiB+)
Due to JupyterLab’s limitations, when you use the file browser to upload files larger than 3 GiB (datasets, checkpoints, etc.), you may encounter network errors. As a workaround, you can upload them through an S3-compatible object storage, for example, the Object Storage service in Nebius AI Cloud:- If you do not have an Object Storage bucket yet, create one.
- Upload your object to the bucket.
-
Get the object’s URL:
- Web console
- In the sidebar, go to
Storage → Object Storage. - Select the bucket in which you uploaded the object.
- In the object’s line, click
→ Get link. The pre-signed URL that includes credentials is copied to the clipboard. It is valid for one hour.
-
In your JupyterLab notebook, use built-in tools like
wgetorcurlto download the file. For example:
Downloading files and notebooks
To download a file or a notebook to your machine:- In the left sidebar, click to open the file browser.
- In the file browser, right-click the file or notebook and click
Download.
“Jupyter” and the Jupyter logos are trademarks or registered trademarks of LF Charities, used by Nebius B.V. with permission.