DOCS-2688: Make switch to modal from models dropdown

docs/services/ml/deploy/tflite_cpu.md

@@ -41,20 +41,18 @@ You can choose to configure your service with an existing model on the machine o
 
 1. To configure your service and deploy a model onto your machine, select **Deploy model on machine** for the **Deployment** field in the resulting ML model service configuration pane.
 
-2. Click on **Select models** to open a dropdown with all of the ML models available to you privately, as well as all of the ML models available in [the registry](https://app.viam.com), which are shared by users.
-   Models that your organization has trained that are not uploaded to the registry will appear first in the dropdown.
-   You can select from any of these models to deploy on your robot.
-   Only TensorFlow Lite models are shown.
+2. Click **Select model**.
+   In the modal that appears, search for models from your organization or the [Registry](/registry/).
 
-{{<imgproc src="/services/deploy-model-menu.png" resize="700x" alt="Models dropdown menu with models from the registry.">}}
+{{<imgproc src="/tutorials/data-management/mlmodel-modal.png" alt="The ML model service configuration modal." resize="500x" >}}
 
-{{% alert title="Tip" color="tip" %}}
-To see more details about a model, open its page in [the registry](https://app.viam.com).
-{{% /alert %}}
+You can select a model to see more details about it, and then select the model to deploy it to your machine.
+
+{{<imgproc src="/tutorials/data-management/mlmodel-service-conf.png" alt="The ML model service configuration modal with a model suggested." resize="450x" >}}
 
 3. Also, optionally select the **Number of threads**.
 
-{{<imgproc src="/services/deploy-model.png" resize="700x" alt="Create a machine learning models service with a model to be deployed">}}
+4. Click **Save** at the top right of the window to save your changes.
 
 {{% /tab %}}
 {{% tab name="Path to Existing Model On Robot" %}}

docs/tutorials/projects/filtered-camera.md

@@ -244,7 +244,8 @@ Add the ML model service to your machine to be able to deploy and update ML mode
 1. Navigate to your machine's **CONFIGURE** tab in the [Viam app](https://app.viam.com).
 1. Click the **+** (Create) button next to your main part in the left-hand menu and select **Service**, then select the built-in `TFLite CPU` model.
 1. Use the suggested name for your service or give it a name, like `my-mlmodel-service`, then click **Create**.
-1. On the panel that appears, select the **Deploy model on machine** toggle, then select your model from the **Select model** dropdown.
+1. On the panel that appears, select the **Deploy model on machine** toggle, then select **Select model**.
+   Select your model from the modal that appears.
    If you don't see your model name appear here, ensure that your model appears under the [**Models** subtab](https://app.viam.com/data/models) of the **DATA** tab in the Viam app.
    If you trained your own model, ensure that the model has finished training and appears under the **Models** section of that page, and not the **Training** section.
 1. Click **Save** in the top right corner of the page to save your changes.

docs/tutorials/projects/integrating-viam-with-openai.md

@@ -255,7 +255,7 @@ To configure an ML model service:
 Your robot will register this as a machine learning model and make it available for use.
 
 Select **Deploy model on machine** for the **Deployment** field.
-Then select the `viam-labs:EfficientDet-COCO` model from the **Models** dropdown.
+Click **Select model**, then select the `viam-labs:EfficientDet-COCO` model from the modal that appears.
 
 Now, create a vision service to visualize your ML model:
 

docs/tutorials/projects/verification-system.md

@@ -93,7 +93,7 @@ The model can detect a variety of things which you can see in <file>[labels.txt]
 3. Select type `ML model`, then select model `TFLite CPU`.
 4. Enter `persondetect` as the name for your ML model service, then click **Create**.
 5. Select **Deploy model on machine** for the **Deployment** field.
-6. Then select the `viam-labs:EfficientDet-COCO` model from the **Select models** dropdown.
+6. Click **Select model**, then select the **EfficientDet-COCO** model by **viam-labs** from the **Registry** tab of the modal that appears.
 
 Finally, configure an `mlmodel` detector vision service to use your new `"persondetect"` ML model:
 

docs/tutorials/services/data-mlmodel-tutorial.md

@@ -230,9 +230,10 @@ To deploy a model to your machine:
 1. Click the **+** icon next to your machine part in the left-hand menu and select **Service**.
 1. Select the `ML model` type, then select the `TFLite CPU` model.
 1. Enter a name or use the suggested name, like `my-mlmodel-service`, for your service and click **Create**.
-1. In the resulting ML Model service configuration pane, select **Deploy model on machine**, then select the model you just trained from the **Select model** dropdown menu.
+1. In the resulting ML Model service configuration pane, select **Deploy model on machine**, then click **Select model**.
+   In the modal that appears, search for and select a model from your organization or the [Registry](/registry/).
 
-   {{< imgproc src="/tutorials/data-management/mlmodel-service-conf.png" alt="The ML model service configuration pane showing the required settings to deploy the my-classifier-model." resize="600x" >}}
+   {{<imgproc src="/tutorials/data-management/mlmodel-service-conf.png" alt="The ML model service configuration pane showing the required settings to deploy the my-classifier-model." resize="400x">}}
 
 1. Click **Save** at the top right of the window to save your changes.