# Browse checkpoint files
<a name="model-checkpoints-saved-file"></a>

Locate checkpoint files using the SageMaker Python SDK and the Amazon S3 console.

**To find the checkpoint files programmatically**

To retrieve the S3 bucket URI where the checkpoints are saved, check the following estimator attribute:

```
estimator.checkpoint_s3_uri
```

This returns the S3 output path for checkpoints configured while requesting the `CreateTrainingJob` request. To find the saved checkpoint files using the S3 console, use the following procedure.

**To find the checkpoint files from the S3 console**

1. Sign in to the AWS Management Console and open the SageMaker AI console at [https://console.aws.amazon.com/sagemaker/](https://console.aws.amazon.com/sagemaker/).

1. In the left navigation pane, choose **Training jobs**.

1. Choose the link to the training job with checkpointing enabled to open **Job settings**.

1. On the **Job settings** page of the training job, locate the **Checkpoint configuration** section.  
![\[Checkpoint configuration section in the Job settings page of a training job.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/checkpoints_trainingjob.png)

1. Use the link to the S3 bucket to access the checkpoint files.