> For the complete documentation index, see [llms.txt](https://docs.datasaur.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.datasaur.ai/assisted-labeling/ml-assisted-labeling/amazon-sagemaker.md).

# Amazon SageMaker

{% hint style="info" %}
**Supported labeling types**: Row labeling.
{% endhint %}

You can integrate your Amazon SageMaker Inference Endpoint for data labeling with **ML-assisted labeling**.

## Enable ML-assisted labeling extension

1. [Create a custom project ](https://datasaurai.gitbook.io/datasaur/nlp-projects/creating-a-project)for row labeling.
2. Click the gear icon from the extension panel to open the **Manage extensions** dialog.
3. Enable the **ML-assisted labeling** extension.

<figure><img src="/files/9KrQiRV1too1I67Qilqd" alt="Image of Manage Extension Pop Up to enable ML assisted"><figcaption><p>Manage extensions dialog</p></figcaption></figure>

4. Once enabled, select **Amazon SageMaker** as the service provider.

<figure><img src="/files/acIvvs1lPbp2nWIDCwaN" alt="Image of ML Assisted with Amazon SageMaker"><figcaption></figcaption></figure>

## Setup role in AWS Identity and Access Management (IAM)

Before creating a role in the **IAM** page, create the required policies to define permissions for the new role.

1. Go to your **IAM** page, navigate to the **Policies** section, and then create a new policy.
2. Download the example below and add it.

{% file src="/files/zFJXgAXxct7lrTKFXifC" %}

After that, proceed to create a new role:

1. Go to the **IAM** page and navigate to the **Roles** section.
2. Click **Create Role**, then select **AWS account** as the role type.
3. Enter the **Account ID** and **External ID**. These values are automatically generated in the Datasaur **ML-assisted labeling** extension and can be copied into AWS.

<figure><img src="/files/XLFyzAxxy1blY5c8wesr" alt="Image of Select trusted entity menu"><figcaption><p>Select trusted entity</p></figcaption></figure>

3. On the **Add permissions** step, search the policy you created before and add them to the permissions.
4. Provide a role name and click **Create role.** You can check the trusted policies config below. The role will be created successfully.

{% file src="/files/uDPoWAE6RkCszEfqglQG" %}

5. View your role and copy the **Role ARN**.

<figure><img src="/files/hnYIBuxdrMrcN4U6RbVP" alt="Image of Role page to copy role ARN"><figcaption></figcaption></figure>

7. Paste this information into the **ML-assisted labeling** extension.
8. Go back to the **Amazon SageMaker** page and retrieve the **Endpoint ARN**. Copy it and paste it into the extension.

<figure><img src="/files/O4xnls8pPrDBrf0m8Mxw" alt="Image of Endpoint Details"><figcaption><p>Endpoint details</p></figcaption></figure>

## Start prediction

Once you have configured the settings, click **Predict labels** to generate predictions from your model.

<figure><img src="/files/OGlNaupjAoGXa0hX8l2p" alt="Image of Prediction result"><figcaption><p>Prediction appears</p></figcaption></figure>