Add Nvidia collections image to documentation

Author: ssalgadodev

articles/ai-foundry/how-to/deploy-nvidia-inference-microservice.md

@@ -59,6 +59,9 @@ Get improved TCO (total cost of ownership) and performance with NVIDIA NIMs offe
 1. Sign in to [Azure AI Foundry](https://ai.azure.com) and go to the **Home** page.
 2. Select **Model catalog** from the left sidebar.
 3. In the filters section, select **Collections** and select **NVIDIA**.
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+:::image type="content" source="../media/how-to/deploy-nvidia-inference-microservice/nvidia-collections.png" alt-text="A screenshot showing the Nvidia inference microservices available in the model catalog." lightbox="../media/how-to/deploy-nvidia-inference-microservice/nvidia-collections.png":::  
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 4. Select the NVIDIA NIM of your choice. In this article, we are using **Llama-3.3-70B-Instruct-NIM-microservice** as an example.
 5. Select **Deploy**.
 6. Select one of the NVIDIA GPU based VM SKUs supported for the NIM, based on your intended workload. You need to have quota in your Azure subscription.
@@ -73,9 +76,6 @@ Get improved TCO (total cost of ownership) and performance with NVIDIA NIMs offe
 
 10. Select the checkbox to acknowledge understanding of pricing and terms of use, and then, select **Deploy**.
 
-:::image type="content" source="../media/how-to/deploy-nvidia-inference-microservice/deploy-nvidia-inference-microservice.png" alt-text="A screenshot showing the deploy model button in the deployment wizard." lightbox="../media/how-to/deploy-nvidia-inference-microservice/deploy-nvidia-inference-microservice.png"::: 
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 ## Consume NVIDIA NIM deployments
 
 After your deployment is successfully created, you can go to **Models + Endpoints** under My assets in your Azure AI Foundry project, select your deployment under "Model deployments" and navigate to the Test tab for sample inference to the endpoint. You can also go to the Chat Playground by selecting **Open in Playground** in Deployment Details tab, to be able to modify parameters for the inference requests.