Doc updates v2 21 (#93)

* rhoai-25155 fix model deploy mode

* rhoai-26059 update text that references saving in ONNX format

* rhoai-24489 change notebook image to workbench image

* undo previous commit

* doc-updates-v2-21 fix title of xref target

* minor fix

* update screencaptures re rhoai-26405

* sme review - update screen capture w red highlight

Author: MelissaFlinn

workshop/docs/modules/ROOT/assets/images/projects/ds-project-create-pipeline-server-form.png

@@ -1,7 +1,7 @@
 [id='creating-a-workbench']
 = Creating a workbench and selecting a workbench image
 
-A workbench is an instance of your development and experimentation environment. When you create a workbench, you select a workbench image (sometimes referred to as a notebook image) that is optimized with the tools and libraries that you need for developing models. 
+A workbench is an instance of your development and experimentation environment. When you create a workbench, you select a workbench image that is optimized with the tools and libraries that you need for developing models. 
 
 .Prerequisites
 
@@ -22,7 +22,7 @@ image::workbenches/ds-project-create-workbench.png[Create workbench button, 800]
 +
 image::workbenches/create-workbench-form-name-desc.png[Workbench name and description, 600]
 +
-{org-name} provides several supported workbench images. In the *Notebook image* section, you can choose one of the default images or a custom image that an administrator has set up for you. The *Tensorflow* image has the libraries needed for this {deliverable}.
+{org-name} provides several supported workbench images. In the *Workbench image* section, you can choose one of the default images or a custom image that an administrator has set up for you. The *Tensorflow* image has the libraries needed for this {deliverable}.
 
 . Select the latest *Tensorflow* image.
 +

workshop/docs/modules/ROOT/assets/images/projects/ds-project-create-pipeline-server.png

@@ -7,11 +7,11 @@ The JupyterLab environment is a web-based environment, but everything you do ins
 
 .Prerequisites
 
-You created a workbench, as described in xref:creating-a-workbench.adoc[Creating a workbench and selecting a Notebook image].
+You created a workbench, as described in xref:creating-a-workbench.adoc[Creating a workbench and selecting a workbench image].
 
 .Procedure
 
-. Click the link for your workbench. If prompted, log in and allow the Notebook to authorize your user.
+. Click the link for your workbench. If prompted, log in and allow JupyterLab to authorize your user.
 +
 image::workbenches/ds-project-workbench-open.png[Open workbench, 400]
 +

workshop/docs/modules/ROOT/assets/images/workbenches/create-workbench-form-image.png

@@ -3,11 +3,7 @@
 
 After you train a model, you can deploy it by using the {productname-short} model serving capabilities.
 
-To prepare a model for deployment, you must complete the following tasks:
-
-* Move the model from your workbench to your S3-compatible object storage. Use the connection that you created in the xref:storing-data-with-connections.adoc[Storing data with connections] section and upload the model from a notebook. 
-
-* Convert the model to the portable ONNX format. ONNX allows you to transfer models between frameworks with minimal preparation and without the need for rewriting the models.
+To prepare a model for deployment, you must move the model from your workbench to your S3-compatible object storage. Use the connection that you created in the xref:storing-data-with-connections.adoc[Storing data with connections] section and upload the model from a notebook. 
 
 .Prerequisites
 
@@ -20,7 +16,7 @@ image::projects/ds-project-connections.png[Data storage in workbench]
 
 . In your JupyterLab environment, open the `2_save_model.ipynb` file.
 
-. Follow the instructions in the notebook to make the model accessible in storage and save it in the portable ONNX format.
+. Follow the instructions in the notebook to make the model accessible in storage.
 
 .Verification
 

workshop/docs/modules/ROOT/assets/images/workbenches/ds-project-workbench-list.png

@@ -7,6 +7,8 @@ In your notebook environment, open the `1_experiment_train.ipynb` file and follo
 
 image::workbenches/jupyter-notebook-1.png[Jupyter Notebook 1]
 
+When you save the model, you convert the model to the portable ONNX format. ONNX allows you to transfer models between frameworks with minimal preparation and without the need for rewriting the models.
+
 .Next step
 
 xref:preparing-a-model-for-deployment.adoc[Preparing a model for deployment]