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guides: update jupyter guide (#20923) 

Signed-off-by: Craig Osterhout <craig.osterhout@docker.com>
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@ -383,39 +383,42 @@ $ docker run --rm -p 8889:8888 YOUR-USER-NAME/my-jupyer-image start-notebook.py
### Share your volume
This example uses the Docker Desktop [Volumes Backup & Share](https://hub.docker.com/extensions/docker/volumes-backup-extension) extension. Alternatively, in the CLI you can [back up the volume](/engine/storage/volumes/#back-up-a-volume) and then [push it using the ORAS CLI](/manuals/docker-hub/oci-artifacts.md#push-a-volume).
This example uses the Docker Desktop graphical user interface. Alternatively, in the command line interface you can [back up the volume](/engine/storage/volumes/#back-up-a-volume) and then [push it using the ORAS CLI](/manuals/docker-hub/oci-artifacts.md#push-a-volume).
1. Install the Volumes Backup & Share extension.
1. Open the Docker Dashboard and select **Extensions**.
2. Search for `Volumes Backup & Share`.
3. In the search results select **Install** for the extension.
2. Open the **Volumes Backup & Share** extension in the Docker Dashboard.
3. Next to the **jupyter-data** volume, select the **Export volume** icon.
4. In the **Export content** window, select **Registry**.
5. In the text box under **Registry**, specify your Docker ID and a name for the
volume. For example, `YOUR-USERNAME/jupyter-data`.
6. Select **Export**.
7. Verify that you exported the volume to Docker Hub.
1. Sign in to Docker Desktop.
2. In the Docker Dashboard, select **Volumes**.
3. Select the **jupyter-data** volume by selecting the name.
4. Select the **Exports** tab.
5. Select **Quick export**.
6. For **Location**, select **Registry**.
7. In the text box under **Registry**, specify your Docker ID, a name for the
volume, and a tag. For example, `YOUR-USERNAME/jupyter-data:latest`.
8. Select **Save**.
9. Verify that you exported the volume to Docker Hub.
1. Go to [Docker Hub](https://hub.docker.com).
2. Select **Repositories**.
3. View the **Last pushed** time for your repository.
Other users can now download and import your volume. To import the volume and then run it with your image:
1. In the Volumes Backup & Share extension, select **Import into new volume**.
2. In the **Import into a new volume** window, select **Registry**.
3. In the text box under **Registry**, specify your Docker ID and the repository
name for the volume. For example, `YOUR-USERNAME/jupyter-data`.
4. In **Volume name**, specify the name you want to give the
volume. This example uses `jupyter-data` as the name.
5. Select **Import**.
6. In a terminal, run `docker run` to run your image with the imported volume.
1. Sign in to Docker Desktop.
2. In the Docker Dashboard, select **Volumes**.
3. Select **Create** to create a new volume.
4. Specify a name for the new volume. For this example, use `jupyter-data-2`.
5. Select **Create**.
6. In the list of volumes, select the **jupyter-data-2** volume by selecting the
name.
7. Select **Import**.
8. For **Location**, select **Registry**.
9. In the text box under **Registry**, specify the same name as the repository
that you exported your volume to. For example,
`YOUR-USERNAME/jupyter-data:latest`.
10. Select **Import**.
11. In a terminal, run `docker run` to run your image with the imported volume.
Replace `YOUR-USER-NAME` with your Docker ID.
```console
$ docker run --rm -p 8889:8888 -v jupyter-data:/home/jovyan/work YOUR-USER-NAME/my-jupyter-image start-notebook.py --NotebookApp.token='my-token'
$ docker run --rm -p 8889:8888 -v jupyter-data-2:/home/jovyan/work YOUR-USER-NAME/my-jupyter-image start-notebook.py --NotebookApp.token='my-token'
```
## Summary