DRAG DROP
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You have a Docker host named Host1 that contains a container base image.
You have an Azure subscription that contains a custom speech-to-text model named model1.
You need to run model1 on Host1.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
1. Request approval to run container 2. Export model1 to Host1 3. Run the container https://learn.microsoft.com/en-us/azure/cognitive-services/speech-service/speech-container-stt?tabs=container&pivots=programming-language-csharp
Okay, this link provides more information about the approval step, but approval is only necessary when you run the container in a disconnected environment. So if that is mentioned in a question, choosing this step will make more sense. https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-container-overview#request-approval-to-run-the-container
No. 1.Export model1 to Host1. 2.Request approval to run the container. 3.Run the container.
you are no. 1. Request approval to run container 2. Export model1 to Host1 3. Run the container
You only need to request approval if you plan to run the container in a completely disconnected environment. And you might not get approved at all as there are some requirements. The question does not indicate if we need to run the container in such a environment.
Based on what you can choose here I would say it’s a disconnected environment. For a connected environment using docker run allows you to download the model at the same so there is no need to export the model manually and then copy it to the host. Zellck is right in the choices.
Probably here we are requested to run the container in a disconnected environmnet so i think correct answer is : Request approval to run container Export model1 to Host1 Run the container https://learn.microsoft.com/en-us/azure/ai-services/containers/disconnected-containers
Not sure. https://learn.microsoft.com/en-us/azure/cognitive-services/speech-service/speech-container-overview#request-approval-to-run-the-container
https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-container-cstt?tabs=custom-model%2Ccontainer&pivots=programming-language-csharp In this article, you'll learn how to download [from Microsoft Container Registry (MCR)], install, and run a Custom speech to text container. Get the model ID (to use as the argument to the ModelId parameter of the docker run command): The custom model has to have been trained by using the Speech Studio. N/a so far, excluding A (Retrain the model).
Run the container with docker run: B (Request approval precedes), The docker run command will start the container when all three of the following options are provided with valid values: ApiKey, Billing, EULA https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-container-howto#billing-arguments D (Run container), C (Get model) Here's an example docker run command with placeholder values. … This command: • Runs a custom speech to text container from the container image. • Allocates 4 CPU cores and 8 GB of memory. • Loads the custom speech to text model from the volume input mount, for example, C:\CustomSpeech. • Exposes TCP port 5000 and allocates a pseudo-TTY for the container. • Downloads the model given the ModelId (if not found on the volume mount).
Request Export Run
this is the answer from Copilot: To run the custom speech-to-text model on your Docker host, you should perform the following actions in sequence: Export model to Host1: You need to export the model from Azure to your Docker host. This typically involves downloading the model and moving it to the Docker host. Run the container: Once the model is on the Docker host, you can run the container that uses this model. Configure disk logging: After the container is running, configure disk logging to keep track of the container's activities and to troubleshoot any issues that might arise.
1. Request approval to run container 2. Export model1 to Host1 3. Run the container