# Compile a Model (Amazon SageMaker AI Console)
Compile Models: Console

You can create an Amazon SageMaker Neo compilation job in the Amazon SageMaker AI console.

1. In the **Amazon SageMaker AI** console, choose **Compilation jobs**, and then choose **Create compilation job**.  
![\[Create a compilation job.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/neo/8-create-compilation-job.png)

1. On the **Create compilation job** page, under **Job name**, enter a name. Then select an **IAM role**.  
![\[Create compilation job page.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/neo/9-create-compilation-job-config.png)

1. If you don’t have an IAM role, choose **Create a new role**.  
![\[Create IAM role location.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/neo/10a-create-iam-role.png)

1. On the **Create an IAM role** page, choose **Any S3 bucket**, and choose **Create role**.  
![\[Create IAM role page.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/neo/10-create-iam-role.png)

1. 

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#### [ Non PyTorch Frameworks ]

   Within the **Input configuration** section, enter the full path of the Amazon S3 bucket URI that contains your model artifacts in the **Location of model artifacts** input field. Your model artifacts must be in a compressed tarball file format (`.tar.gz`). 

   For the **Data input configuration** field, enter the JSON string that specifies the shape of the input data.

   For **Machine learning framework**, choose the framework of your choice.

![\[Input configuration page.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/neo/neo-create-compilation-job-input-config.png)


   To find the JSON string examples of input data shapes depending on frameworks, see [What input data shapes Neo expects](https://docs.aws.amazon.com/sagemaker/latest/dg/neo-troubleshooting.html#neo-troubleshooting-errors-preventing).

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#### [ PyTorch Framework ]

   Similar instructions apply for compiling PyTorch models. However, if you trained with PyTorch and are trying to compile the model for `ml_*` (except `ml_inf`) target, you can optionally specify the version of PyTorch you used.

![\[Example Input configuration section showing where to choose the Framework version.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/neo/compile_console_pytorch.png)


   To find the JSON string examples of input data shapes depending on frameworks, see [What input data shapes Neo expects](https://docs.aws.amazon.com/sagemaker/latest/dg/neo-troubleshooting.html#neo-troubleshooting-errors-preventing).

**Notes**  
If you saved your model by using PyTorch version 2.0 or later, the **Data input configuration field** is optional. SageMaker Neo gets the input configuration from the model definition file that you create with PyTorch. For more information about how to create the definition file, see the [PyTorch](neo-compilation-preparing-model.md#how-to-save-pytorch) section under *Saving Models for SageMaker AI Neo*.
When compiling for `ml_*` instances using PyTorch framework, use **Compiler options** field in **Output Configuration** to provide the correct data type (`dtype`) of the model’s input. The default is set to `"float32"`. 

![\[Example Output Configuration section.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/neo/neo_compilation_console_pytorch_compiler_options.png)


**Warning**  
 If you specify a Amazon S3 bucket URI path that leads to `.pth` file, you will receive the following error after starting compilation: `ClientError: InputConfiguration: Unable to untar input model.Please confirm the model is a tar.gz file` 

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1.  Go to the **Output configuration** section. Choose where you want to deploy your model. You can deploy your model to a **Target device** or a **Target platform**. Target devices include cloud and edge devices. Target platforms refer to specific OS, architecture, and accelerators you want your model to run on. 

    For **S3 Output location**, enter the path to the S3 bucket where you want to store the model. You can optionally add compiler options in JSON format under the **Compiler options** section.   
![\[Output configuration page.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/neo/neo-console-output-config.png)

1. Check the status of the compilation job when started. This status of the job can be found at the top of the **Compilation Job** page, as shown in the following screenshot. You can also check the status of it in the **Status** column.  
![\[Compilation job status.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/neo/12-run-model-compilation.png)

1. Check the status of the compilation job when completed. You can check the status in the **Status** column as shown in the following screenshot.  
![\[Compilation job status.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/neo/12a-completed-model-compilation.png)