Deploying a Hugging Face Model to Amazon SageMaker

Deploying a Hugging Face Model to Amazon SageMaker

This tutorial will guide you through the process of deploying a Hugging Face model to Amazon SageMaker. By following these steps, you'll be able to host your model on a scalable and reliable platform.

Prerequisites

Before getting started, make sure you have the following:

  1. Create a SageMaker domain in the AWS Console.
  2. Create an IAM account with SageMaker admin access and generate an access key.
  3. Create an IAM role with SageMaker admin access.

Setup

Install AWS CLI

Install the AWS Command Line Interface (CLI) on your local machine. You can follow the official AWS documentation for installation instructions specific to your operating system.

Configure AWS CLI

Run the following command in your terminal:

aws configure

Enter the access key created earlier and specify your AWS region when prompted.

Deployment

  1. Go to the Hugging Face website and find the model you want to deploy.
  2. Click on the deploy button and copy the template code provided.
  3. Open Visual Studio Code (VSCode) and create a new file.
  4. Paste the template code from Hugging Face into the file.
  5. Modify the role name in the code to match the IAM role you created earlier:
role = iam.get_role(RoleName='YOUR_ROLE_NAME_HERE')['Role']['Arn']
  1. Save the file as sagemaker_deploy.py.
  2. Run the sagemaker_deploy.py script to deploy your model to SageMaker.

Verification

  1. Open the SageMaker console in the AWS Management Console.
  2. Verify that the model has been successfully deployed and the endpoint is active.

Inference

  1. Create a new file in VSCode and name it sagemaker_infer.py.
  2. Write your inference code in the sagemaker_infer.py file to make predictions using the deployed model.
  3. Run the sagemaker_infer.py script to perform inference.

Congratulations! You have successfully deployed a Hugging Face model to Amazon SageMaker. Feel free to explore and experiment with your deployed model.

Additional Resources

If you have any questions or need some guidance on how to do this at scale please get in touch. Happy deploying and have fun!