{"id":2473,"date":"2023-12-26T12:03:42","date_gmt":"2023-12-26T12:03:42","guid":{"rendered":"https:\/\/learning.workfall.com\/learning\/blog\/?p=2473"},"modified":"2025-09-11T06:58:59","modified_gmt":"2025-09-11T06:58:59","slug":"crafting-captivating-narratives-the-power-of-gen-ai-with-sagemaker","status":"publish","type":"post","link":"https:\/\/learning.workfall.com\/learning\/blog\/crafting-captivating-narratives-the-power-of-gen-ai-with-sagemaker\/","title":{"rendered":"Crafting Captivating Narratives: The Power of Gen AI with SageMaker"},"content":{"rendered":"<span class=\"rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">Reading Time: <\/span> <span class=\"rt-time\">14<\/span> <span class=\"rt-label rt-postfix\">minutes<\/span><\/span>\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Illustrations\/1.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">In the evolving landscape of AI-driven innovation, crafting compelling narratives has reached new heights with the power of Generative AI, and Amazon SageMaker stands as a pivotal platform for realizing this potential.<\/p>\n\n\n\n<p class=\"has-text-align-justify\">This hands-on exploration will guide you through harnessing the capabilities of Generative AI, specifically the GPT-2 model, to craft engaging stories from incomplete sentences using Amazon SageMaker Studio.<\/p>\n\n\n\n<p class=\"has-text-align-justify\">The step-by-step guide ensures a seamless setup by walking you through AWS Console navigation, region configuration, IAM permissions setup, and the establishment of a SageMaker Studio domain for single-user deployment.<\/p>\n\n\n\n<p class=\"has-text-align-justify\">As you delve into the intricacies of SageMaker Studio, the tutorial directs you to the HuggingFace hub, where you choose the GPT-2 model and deploy it with ease.<\/p>\n\n\n\n<p class=\"has-text-align-justify\">The subsequent testing phase allows you to execute code for text generation, providing a dynamic experience as you observe the model&#8217;s diverse narrations for various incomplete sentences.<\/p>\n\n\n\n<p class=\"has-text-align-justify\">Crucially, the tutorial concludes with a comprehensive cleanup process to avoid unnecessary charges, emphasizing the responsible utilization of cloud resources.<\/p>\n\n\n\n<p class=\"has-text-align-justify\">This immersive journey not only showcases the potential of Generative AI but also equips you with the skills to navigate <a href=\"https:\/\/learning.workfall.com\/learning\/blog\/how-to-build-machine-learning-models-quickly-using-amazon-sagemaker\/\">SageMaker<\/a> efficiently, ensuring a seamless integration into your business use case.<\/p>\n\n\n\n<h2>Hands-on<\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Illustrations\/2.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">In this hands-on experience, discover the world of Generative AI and learn to create captivating stories from incomplete sentences using <a href=\"https:\/\/learning.workfall.com\/learning\/blog\/how-to-build-ml-models-to-generate-accurate-predictions-without-writing-code-using-amazon-sagemaker-canvas\/\">Amazon SageMaker Studio<\/a> and the GPT-2 model.<\/p>\n\n\n\n<p class=\"has-text-align-justify\">The comprehensive journey provided in this implementation will guide you step by step, demonstrating how to effectively use Generative AI to craft engaging narratives. Follow the detailed guide not only for setting up but also for performing a thorough cleanup to ensure you avoid unnecessary charges.<\/p>\n\n\n\n<p>Explore the flexibility of Generative AI and unleash your storytelling potential with this hands-on.<\/p>\n\n\n\n<p><strong>Step 1: Navigate to AWS Console<\/strong><\/p>\n\n\n\n<ul><li>Log in to the AWS dashboard to access the AWS Console.<\/li><\/ul>\n\n\n\n<p><strong>Step 2: Change Region and Set IAM Permissions<\/strong><\/p>\n\n\n\n<ul><li>Change the region to US East (N. Virginia) or as per your requirements.<\/li><\/ul>\n\n\n\n<ul><li>Search for IAM service, navigate to its dashboard, and select Users.<\/li><\/ul>\n\n\n\n<ul><li>Choose the user to which you&#8217;ll add permissions. Scroll to the permissions tab and click on &#8220;Add permissions.&#8221;<\/li><\/ul>\n\n\n\n<ul><li>Select &#8220;Attach policies directly&#8221; and search for the SageMaker service.<\/li><\/ul>\n\n\n\n<ul><li>Provide full access to Amazon SageMaker for the IAM user (adjust as needed) and complete the setup.<\/li><\/ul>\n\n\n\n<p><strong>Step 3: Setup SageMaker Studio<\/strong><\/p>\n\n\n\n<ul><li>Search for the Amazon SageMaker service and navigate to its dashboard.<\/li><\/ul>\n\n\n\n<ul><li>In the left navigation pane, select &#8220;Domains&#8221; and click on &#8220;Create domain.&#8221;<\/li><\/ul>\n\n\n\n<ul><li>Choose to set up a domain for a single user and proceed with the setup.<\/li><\/ul>\n\n\n\n<ul><li>Once created, click on the domain, select the default user, and launch SageMaker Studio.<\/li><\/ul>\n\n\n\n<p><strong>Step 4: Explore SageMaker Studio<\/strong><\/p>\n\n\n\n<ul><li>In SageMaker Studio, select the &#8220;JumpStart&#8221; option from the left navigation pane.<\/li><\/ul>\n\n\n\n<ul><li>Explore different hubs, and for this hands-on, choose the GPT-2 model from the HuggingFace hub.<\/li><\/ul>\n\n\n\n<ul><li>Navigate to the GPT-2 model, evaluate its features, and click on &#8220;Deploy&#8221; for deployment.<\/li><\/ul>\n\n\n\n<p><strong>Step 5: Deploy the Model<\/strong><\/p>\n\n\n\n<ul><li>Set up deployment parameters, including the endpoint name and instance type.<\/li><\/ul>\n\n\n\n<ul><li>Click on &#8220;Deploy,&#8221; and on success, the endpoint status will be &#8220;In Service.&#8221;<\/li><\/ul>\n\n\n\n<ul><li>Access the Studio and start working on the deployed model.<\/li><\/ul>\n\n\n\n<p><strong>Step 6: Test Text Generation<\/strong><\/p>\n\n\n\n<ul><li>Open the notebook and execute the provided code for text generation.<\/li><\/ul>\n\n\n\n<ul><li>Experiment by changing input sentences and regenerate the output.<\/li><\/ul>\n\n\n\n<ul><li>Observe different narrations generated by the model for incomplete sentences.<\/li><\/ul>\n\n\n\n<p><strong>Step 7: Cleanup to Avoid Charges<\/strong><\/p>\n\n\n\n<ul><li>Head to the SageMaker dashboard, click on &#8220;Models,&#8221; select the deployed model, and delete it.<\/li><\/ul>\n\n\n\n<ul><li>Delete the endpoint configurations and endpoints created during the hands-on.<\/li><\/ul>\n\n\n\n<ul><li>Cleanup the <a href=\"https:\/\/learning.workfall.com\/learning\/blog\/how-to-create-and-mount-an-amazon-efs-file-system-using-amazon-ec2-launch-instance-wizard\/\">EFS<\/a> created by searching for the EFS service and deleting the file system.<\/li><\/ul>\n\n\n\n<ul><li>Finally, delete the domain by removing the default user, deleting apps, and removing the domain.<\/li><\/ul>\n\n\n\n<ul><li>Manually delete the <a href=\"https:\/\/learning.workfall.com\/learning\/blog\/send-s3-event-notification-email-using-lambda-and-ses\/\">S3<\/a> bucket created for the domain to complete the cleanup.<\/li><\/ul>\n\n\n\n<p>Navigate to the AWS console by logging in to the dashboard.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/1.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">First, let&#8217;s change the region in which we will be performing the hands-on. Select region as per your requirements from the drop-down. In our case, we will select the US East (N. Virginia) region.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/2.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>On success, you will see the following region chosen.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/3.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>In the search box, search for the IAM service. Click on it to navigate to its dashboard.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/4.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>You will then navigate to the screen as shown in the image below. Select Users from the left navigation pane.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/5.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">You will then see the list of users on the dashboard. Click on the user to which you need to add the permissions. To perform the hands-on, we need to add some permissions to the IAM user.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/6.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>Scroll down to the permissions tab. Click on Add permissions.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/7.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>Select Add permissions.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/8.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>Select the Attach policies directly option.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/9.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>In the search box, search for the SageMaker service.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/10.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">For this hands-on, we will be providing full access to Amazon SageMaker for the IAM user. You can limit the access as per the requirement and that is recommended. Just for the demo purpose we will be providing the entire access.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/11.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>On the bottom of the screen, click on Next.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/12.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>Review the same and click on Add permissions.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/13.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>On success, you&#8217;ll see the screen as shown below.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/14.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>Now, if you will see the permissions tab, you will see a new policy added.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/15.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>In the search bar, search for the Amazon SageMaker service. Click on it to navigate to its dashboard.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/16.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">You will see the page displayed as shown in the image below. Now, as a prerequisite, we first need to create a domain to start a SageMaker studio.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/17.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>To do so, in the left navigation pane, select the domains option.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/18.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>In the domain homepage, click on create domain.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/19.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">You will be provided with 2 options. You can either set up a domain for a single user which is basically a quick setup process or you can set it up for an organization. In our case, for the hands-on, since we just need one user to have access, we will select the set up for a single user approach. Select the same and click on the setup button.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/20.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Setting up a domain takes some time. It might take a few minutes. You will be shown the process bar as displayed in the image below.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/21.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">In successful creation, you will see the success message along with the domain entity in the list of domains. Now to start the studio, click on the domain. Under the User profiles tab, you will see the default user created. Click on the default user.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/22.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>You will then be navigated to the details page of the default user. Click on launch.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/23.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>Select the studio option.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/24.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>You will be navigated to the SageMaker studio in a new tab.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/25.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>In the left navigation pane, select the jumpstart option.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/26.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">You will then see a list of hubs as shown in the image below. Now the models are divided as per the hubs who are basically the owner of the different models.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/27.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">We will be using the GPT 2 models of HuggingFace hub for text completion\/generation use cases. You can either click on the HuggingFace hub and search for the GPT 2 model or you can use the search feature in the outer menu to search for the model. In the search bar, enter gpt2 and you will see the model filtered. Click on the GPT 2 model.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/28.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">You will be navigated to the details page of the model. On the same page, you are provided with the details of what the model can be used for and what all features it provides along with examples. You will also see the number of likes and downloads for the model. The model provides 2 options. <\/p>\n\n\n\n<p class=\"has-text-align-justify\">Either we can evaluate the accuracy of the model clicking on the Evaluate button and setting up the metrics or we can deploy and use the model clicking on the Deploy button. For our use case, we will use the Deploy feature. Click on the Deploy button.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/29.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>You will then be navigated to the configuration page where we need to set up the deployment parameters.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/30.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">For the Endpoint settings, you can either use the default endpoint or from the drop-down, you can click on the Enter endpoint name option.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/31.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Type in a name for the Endpoint as you can see in the image below. Select the Instance type and the count as per your requirements. For the demo purpose, we will just be using 1 instance of ml.g5.2xlarge.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/32.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">You can leave the Advanced options to default if you are trying out the service following our demo or you can set it up accordingly as per your requirements. Once done, scroll down and click on Deploy.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/33.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>On success, you will see the endpoint status as in service which means it&#8217;s ready for usage.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/34.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>In the same modal below the endpoint status, you will see the deployed model details.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/35.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>Below that, you will see an option to navigate to the Studio and start working on it.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/36.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>The entire success message looks like as shown in the image below. Click on the Open Notebook button.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/37.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">You will be navigated to the notebook of the Text Generation model with some filled in code as shown in the image below.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/38.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>Click on the first editor box and press Ctrl + Enter to execute the same. The same imports will then be executed.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/39.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Click on the second editor box wherein we need to initialize variables with text on which the model will run and generate a completed sentence as per the requirements. Press Ctrl + Enter to execute the same.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/40.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Now comes the main code that uses the model to complete the input sentences. Press Ctrl + Enter for the same editor box. The code uses the endpoint that we configured while doing the deployment and the input sentences and gives the result as a completed sentence.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/41.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">On success, you will see the output as shown in the image below. The model takes in the input of incomplete sentences and provides an output completing those sentences as shown below highlighted in bold. This in turn shows that the model ran successfully and completed and incomplete sentence narrating a story for the same. On reading the completed sentence, you will figure out that the completed sentence generated by the model narrates a story.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/42.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Now, every time we execute the same code, we will get a different narration completing the incomplete sentences. Execute the code and on checking the output, you will see the new story narrated completing the incomplete sentences.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/43.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Now, let&#8217;s change the input sentences and regenerate the output completing some different and new incomplete sentences. For the input texts in variables text1 and text2, click on the editor box and add incomplete sentences in both the variables as shown in the image below. Click Ctrl + Enter to initialize the variables with the new incomplete sentences.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/44.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Click on the box with the code to regenerate the output. On success, you will see that the model would generate the output completing the incomplete sentences as shown in the image below.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/45.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Execute the text generation code and let&#8217;s see if it generates new output. On execution, you will see that the output generated would be a complete new text completed sentence. Thus, we can successfully conclude that the model generates output as per the need and narrates a story completing the incomplete sentences.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/46.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Now that we have tested out everything and since this execution was for a demo purpose, we need to perform a thorough cleanup to avoid unnecessary charges. In case you followed out hands-on to test out the same, please follow the below steps to perform a thorough cleanup. On the Amazon SageMaker dashboard, click on the models options in the left navigation pane.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/47.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>On the screen, you would see the model you deployed on the SageMaker Studio dashboard.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/48.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>Select the model that is to be deleted and click on Actions and Delete.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/49.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>A modal will pop up. Click on Delete.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/50.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Now that the model is deleted, the next step is to navigate to the Endpoint configurations and delete the same. Click on the Endpoint configurations in the left navigation pane.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/51.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>You will see the same endpoint that you created above on the screen as shown in the image below.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/52.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>Select the same, click on Actions and click Delete.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/53.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>On the popped up modal, click on the Delete button.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/54.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>Now, navigate to the Endpoints dashboard clicking on the Endpoints option in the left navigation pane.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/55.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>You will see the list of Endpoints.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/56.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>Select the Endpoints, click on Actions and click on Delete.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/57.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>On the modal, click on the Delete button.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/58.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Now, we need to clean up the EFS created since deleting the domain does not delete the EFS created. Search for the EFS service and click on it.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/59.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>On the dashboard you will see the file system created. Select the file system and click on the Delete button.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/60.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>In the popped up modal, enter the file system id to confirm the deletion and click on Confirm.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/61.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Finally, navigate back to the Amazon SageMaker and click on Domains in the left navigation pane. You will see the domain we created. Click on the domain.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/62.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">You will be navigated to the Domain details page. Now, to delete a domain, we first need to delete the default user. Click on the default user under the User profiles page.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/63.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">To be able to delete the user, we first need to delete all the apps. Scroll right under the Apps modal and you will see a Delete button. Click on it to delete the app. Once done, you will see the Status column changed from Ready to Deleted. Now, click on the Edit button on the bottom of the page.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/64.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>On the Edit page of the user, click on Delete user.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/65.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>Click on the Yes, delete user button, type delete and finally click on the Delete button.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/66.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Now that we deleted the user, we can delete the Domain. Go to the Domain settings section on the domain details page. Click on the Edit button.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/67.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>Click on the Delete domain button on the domain\u2019s edit page.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/68.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Click the Yes, delete my Domain button, type delete and click on the Delete button. Now, you will see that while deleting the domain as the last step, it states that the S3 bucket created for it won&#8217;t be deleted. So, we need to delete the S3 buckets manually.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/69.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>Search for the S3 service and click on it to navigate to its dashboard.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/70.png\" alt=\"Crafting Captivating Narratives: The Power of Gen AI with SageMaker\"\/><\/figure>\n\n\n\n<p>Select the bucket that was created. Click on the Empty button.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/71.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>To confirm the deletion, enter the bucket name and click on the Delete bucket button.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img src=\"https:\/\/workfall-techblogs.s3.ap-southeast-1.amazonaws.com\/185\/Images\/72.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-justify\">Now that we have deleted and cleaned up everything in regards to the hands-on, we won&#8217;t be charged anything extra and will only be charged for what we used as per the duration of usage.<\/p>\n\n\n\n<h2>Conclusion<\/h2>\n\n\n\n<p class=\"has-text-align-justify\">In conclusion, our technical blog took you through a hands-on journey into the realm of Generative AI using Amazon SageMaker Studio and the GPT-2 model. We provided a comprehensive guide, walking you through each step to effectively leverage Generative AI for crafting engaging narratives.<\/p>\n\n\n\n<p class=\"has-text-align-justify\">We began by navigating to the AWS Console, changing regions, and setting up IAM permissions to ensure a smooth process. Moving on, we explored the setup of SageMaker Studio, creating a domain for a single user, and launching the studio. The blog detailed the exploration of SageMaker Studio, focusing on the GPT-2 model from the HuggingFace hub, and demonstrated how to deploy the model successfully.<\/p>\n\n\n\n<p class=\"has-text-align-justify\">The implementation then guided you through testing text generation, where you could experiment with different input sentences and observe the diverse narrations generated by the GPT-2 model for incomplete sentences.<\/p>\n\n\n\n<p class=\"has-text-align-justify\">To wrap up the hands-on experience responsibly, we emphasized the importance of cleanup to avoid unnecessary charges. This involved deleting the deployed model, endpoint configurations, and endpoints, as well as cleaning up the EFS and S3 bucket created during the process.<\/p>\n\n\n\n<p class=\"has-text-align-justify\">By following our step-by-step guide, you not only gained practical insights into Generative AI but also learned the essential cleanup procedures, ensuring a seamless and cost-effective experience with Amazon SageMaker Studio and the GPT-2 model. We will come up with more such use cases in our upcoming blogs.<\/p>\n\n\n\n<p><strong>Meanwhile\u2026<\/strong><\/p>\n\n\n\n<p class=\"has-text-align-justify\">If you are an aspiring AI enthusiast and want to explore more about the above topics, here are a few of our blogs for your reference:<\/p>\n\n\n\n<ul><li><a href=\"https:\/\/learning.workfall.com\/learning\/blog\/build-ai-apps-with-amazon-partyrock-and-amazon-bedrock\/\">Build AI Apps with Amazon PartyRock and Amazon Bedrock<\/a><\/li><li><a href=\"https:\/\/learning.workfall.com\/learning\/blog\/amazon-partyrock-a-playground-for-generative-ai-enthusiasts\/\">Amazon PartyRock: A Playground for Generative AI Enthusiasts<\/a><\/li><li><a href=\"https:\/\/learning.workfall.com\/learning\/blog\/category\/ai-ml\/\">How to Use ChatGPT API to Create an AI-Powered Web Application That Assists Software Engineers\u2019 Productivity?<\/a><\/li><\/ul>\n\n\n\n<p>Stay tuned to get all the updates about our upcoming blogs on the cloud and the latest technologies.<\/p>\n\n\n\n<p><strong>Keep Exploring -&gt; Keep Learning -&gt; Keep Mastering&nbsp;<\/strong><\/p>\n\n\n\n<p class=\"has-text-align-justify\">At <a href=\"https:\/\/www.workfall.com\/\">Workfall<\/a>, we strive to provide the best tech and pay opportunities to kickass coders around the world. If you\u2019re looking to work with global clients, build cutting-edge products, and make big bucks doing so, give it a shot at <a href=\"https:\/\/app.workfall.com\/partner\/signup\">workfall.com\/partner<\/a> today!<\/p>\n\n\n<style type=\"text\/css\"><\/style><section id='' \n                class='helpie-faq accordions faq-toggle open-first groupSettings-473__enabled' \n                data-collection='' \n                data-pagination='0' \n                data-search='0' \n                data-pagination-enabled='0'\n                role='region'\n                aria-label='FAQ Section'\n                aria-live='polite'><h3 class=\"collection-title\">Frequently Asked Questions:<\/h3><article class=\"accordion \"><div class='helpie-faq-row'><div class='helpie-faq-col helpie-faq-col-12' ><ul><li class=\"accordion__item \"><div class=\"accordion__header \" \r\n                id=\"accordion-header-post-2589\"\r\n                role=\"button\"\r\n                aria-expanded=\"false\"\r\n                aria-controls=\"accordion-content-post-2589\"\r\n                data-id=\"post-2589\" \r\n                data-item=\"hfaq-post-2589\" \r\n                style=\"background:transparent;\" \r\n                data-tags=\"\"\r\n                tabindex=\"0\"><div class=\"accordion__title\">Q: What is Generative AI and why use Amazon SageMaker for story generation?<\/div><\/div><div id=\"accordion-content-post-2589\" \r\n                class=\"accordion__body\" \r\n                role=\"region\"\r\n                aria-labelledby=\"accordion-header-post-2589\"\r\n                style=\"background:transparent;\"><p><span class=\"rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">Reading Time: <\/span> <span class=\"rt-time\">14<\/span> <span class=\"rt-label rt-postfix\">minutes<\/span><\/span><strong>A:<\/strong> <span style=\"font-weight: 400\">Generative AI creates new content based on learned patterns from training data. Amazon SageMaker provides a managed platform to deploy and scale AI models like GPT-2 efficiently, offering seamless integration with AWS services and simplified model deployment for text generation tasks.<\/span><\/p>\n<\/div><\/li><li class=\"accordion__item \"><div class=\"accordion__header \" \r\n                id=\"accordion-header-post-2590\"\r\n                role=\"button\"\r\n                aria-expanded=\"false\"\r\n                aria-controls=\"accordion-content-post-2590\"\r\n                data-id=\"post-2590\" \r\n                data-item=\"hfaq-post-2590\" \r\n                style=\"background:transparent;\" \r\n                data-tags=\"\"\r\n                tabindex=\"0\"><div class=\"accordion__title\">Q: How do I set up the necessary IAM permissions for SageMaker Studio?<\/div><\/div><div id=\"accordion-content-post-2590\" \r\n                class=\"accordion__body\" \r\n                role=\"region\"\r\n                aria-labelledby=\"accordion-header-post-2590\"\r\n                style=\"background:transparent;\"><p><span class=\"rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">Reading Time: <\/span> <span class=\"rt-time\">14<\/span> <span class=\"rt-label rt-postfix\">minutes<\/span><\/span><span style=\"font-weight: 400\"><strong>A:<\/strong> Navigate to the IAM service in AWS Console, select your user, click &#8220;Add permissions,&#8221; choose &#8220;Attach policies directly,&#8221; and search for SageMaker. Add the AmazonSageMakerFullAccess policy (or more restrictive permissions based on your security requirements) to enable SageMaker Studio operations.<\/span><\/p>\n<\/div><\/li><li class=\"accordion__item \"><div class=\"accordion__header \" \r\n                id=\"accordion-header-post-2591\"\r\n                role=\"button\"\r\n                aria-expanded=\"false\"\r\n                aria-controls=\"accordion-content-post-2591\"\r\n                data-id=\"post-2591\" \r\n                data-item=\"hfaq-post-2591\" \r\n                style=\"background:transparent;\" \r\n                data-tags=\"\"\r\n                tabindex=\"0\"><div class=\"accordion__title\">Q: What are the key steps to deploy a GPT-2 model using SageMaker JumpStart?<\/div><\/div><div id=\"accordion-content-post-2591\" \r\n                class=\"accordion__body\" \r\n                role=\"region\"\r\n                aria-labelledby=\"accordion-header-post-2591\"\r\n                style=\"background:transparent;\"><p><span class=\"rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">Reading Time: <\/span> <span class=\"rt-time\">14<\/span> <span class=\"rt-label rt-postfix\">minutes<\/span><\/span><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Create a SageMaker Studio domain for single user setup<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Launch SageMaker Studio and navigate to JumpStart<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Select the GPT-2 model from HuggingFace hub<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Configure deployment parameters (endpoint name, instance type like ml.g5.2xlarge)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Click Deploy and wait for &#8220;In Service&#8221; status<\/span><\/li>\n<\/ul>\n<\/div><\/li><li class=\"accordion__item \"><div class=\"accordion__header \" \r\n                id=\"accordion-header-post-2593\"\r\n                role=\"button\"\r\n                aria-expanded=\"false\"\r\n                aria-controls=\"accordion-content-post-2593\"\r\n                data-id=\"post-2593\" \r\n                data-item=\"hfaq-post-2593\" \r\n                style=\"background:transparent;\" \r\n                data-tags=\"\"\r\n                tabindex=\"0\"><div class=\"accordion__title\">Q: How does the GPT-2 model generate different narratives for the same input?<\/div><\/div><div id=\"accordion-content-post-2593\" \r\n                class=\"accordion__body\" \r\n                role=\"region\"\r\n                aria-labelledby=\"accordion-header-post-2593\"\r\n                style=\"background:transparent;\"><p><span class=\"rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">Reading Time: <\/span> <span class=\"rt-time\">14<\/span> <span class=\"rt-label rt-postfix\">minutes<\/span><\/span><span style=\"font-weight: 400\"><strong>A:<\/strong> The GPT-2 model uses probabilistic text generation, meaning it doesn&#8217;t produce identical outputs for the same input. Each execution samples from probability distributions of possible next words, resulting in creative variations and diverse story completions even when given identical incomplete sentences.<\/span><\/p>\n<\/div><\/li><\/ul><\/div><\/div><\/article><\/section>\n","protected":false},"excerpt":{"rendered":"<p><span class=\"rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">Reading Time: <\/span> <span class=\"rt-time\">14<\/span> <span class=\"rt-label rt-postfix\">minutes<\/span><\/span> In the evolving landscape of AI-driven innovation, crafting compelling narratives has reached new heights with the power of Generative AI, and Amazon SageMaker stands as a pivotal platform for realizing this potential. This hands-on exploration will guide you through harnessing the capabilities of Generative AI, specifically the GPT-2 model, to craft engaging stories from incomplete [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":2474,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"spay_email":""},"categories":[2],"tags":[234,126,129,150,3,465,405,6],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v19.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Crafting Captivating Narratives: The Power of Gen AI with SageMaker - The Workfall Blog<\/title>\n<meta name=\"description\" content=\"Unleash the power of Generative AI with our latest blog on Amazon SageMaker! 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