# How to Mount Datasets in a Gradient Notebook

Notebooks are a web-based Jupyter IDE with shared persistent storage for long-term development and inter-notebook collaboration, backed by accelerated compute.

## Mount Datasets in a Notebook

The dashboard supports mounting datasets for exploring data and training models. On the **datasets** tab, you can mount existing team datasets, public datasets, and create new team datasets.

You can mount a dataset by clicking the **MOUNT** button next to either the team or public dataset you want to use.

![Running Jupyter notebook with file browser and multiple code cells visible.](https://docs.digitalocean.com/screenshots/paperspace/mount-public-dataset.b4bd44acd6e6d4fc81028444ce3aa23ee80c48b554fe23b5fa135cd764ea8350.gif)

When mounting a team dataset, this only mounts the latest version of a dataset. You can change the version of the dataset in the **Advanced Settings** section.

## Add Small Datasets to a Notebook

To add a new dataset, click the **+** icon, then name, describe, and upload the data. You can close the window once the upload has started, as the process continues to happen in the background.

![Dataset upload window showing files being added to a team dataset with drag-and-drop upload area.](https://docs.digitalocean.com/screenshots/paperspace/uploading-files-to-dataset.51461a75a8d33e99a83f29318f979ba98e2c563c8f451ecef62ab1cc0554f4d9.gif)

## Adding Large Datasets (5 GB+) to a Notebook

To create datasets larger than 5 GB, you can use the CLI through the terminal.

```shell
$ gradient datasets create --name democli --storageProviderId ssfe843ndkjdsnr
Created dataset: dsr5zdx0thjhfe2
```

All Gradient datasets are versioned, so if you want to make any changes to data in a dataset, you need to create a new version. The following command creates a new version of your dataset.

```shell
$ gradient datasets versions create --id dst364npcw6ccok
Created dataset version: dst364npcw6ccok:fo5rp4m
```

Once the new version is created, you can then add files to the dataset version.

```shell
$ gradient datasets files put --id dst364npcw6ccok:fo5rp4m --source-path ./some-data/
```

Once all your files are uploaded to the new version, commit the version to the dataset.

```shell
$ gradient datasets versions commit --id dst364npcw6ccok:fo5rp4m
Committed dataset version: dst364npcw6ccok:fo5rp4m
```

Once the dataset version is committed, the data is available in the UI, and you can reference it in other Gradient services such as Notebooks, Workflows, and Deployments.

## Datasets Advanced Settings

To access the settings file that manages all mounted datasets, go to `.gradient/settings.yaml` where you can see all of the mounted datasets and their arguments. You should only use this file for the following:

If you want to change the version of the dataset that is mounted, you have to change the `version-id` of the dataset.

```yaml
integrations:
  quarterly-reports: # mounts in /datasets/quarterly-reports
    type: dataset # denotes a paperspace dataset
    id: dataset-id # a paperspace dataset id
    version: version-id # a paperspace version id
  my-bucket-data: # mounts in /datasets/my-bucket-data
    type: s3 # an s3 bucket
    url: s3://my-bucket/my-data # your s3 bucket url
    accessKeyId: AK123 # your s3 access key id
    secretAccessKey: secret:my-bucket-secret-key # a paperspace secret with your s3 secret key
    region: "us-west-1" # the aws region your bucket is in, if not in aws set "endpoint"
    endpoint: "https://my-bucket-host.com" # a custom bucket host, do not set region if set
```