quickstart update

Author: aahill

articles/cognitive-services/language-service/custom-classification/includes/quickstarts/language-studio.md

@@ -4,7 +4,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: language-service
 ms.topic: include
-ms.date: 02/02/2022
+ms.date: 02/11/2022
 ms.author: aahi
 ms.custom: language-service-custom-classification, ignite-fall-2021
 ---
@@ -64,7 +64,8 @@ Before you can use custom text classification, you will need to create an Azure
     >[!TIP]
     > Your dataset doesn't have to be entirely in the same language. You can have multiple files, each with different supported languages. If your dataset contains files of different languages or if you expect different languages during runtime, select **enable multi-lingual dataset** when you enter the basic information for your project.
 
-7. Select the container where you have uploaded your data. For this quickstart, we will use the existing tags file available in the container. Then click **Next**.
+7. Select the container where you’ve uploaded your data. When asked if your files are already tagged with classes, select **Yes** and choose the available file. Then click **Next**.
+
 
 8. Review the data you entered and select **Create Project**.
 
@@ -90,7 +91,7 @@ After your model is deployed, you can start using it for text classification. Us
 
 2. Select the model you want to test.
 
-3. Add your text to the textbox, you can also upload a `.txt` file. 
+3. Using one of the files you downloaded earlier, add the file's text to the textbox. You can also upload a `.txt` file. 
 
 4. Click on **Run the test**.
 

articles/cognitive-services/language-service/custom-named-entity-recognition/includes/quickstarts/language-studio.md

@@ -74,7 +74,7 @@ Once your resource and storage container are configured, create a new conversati
 
 5. Enter the project information, including a name, description, and the language of the files in your project. You won’t be able to change the name of your project later. 
 
-6. Select the container where you’ve uploaded your data. For this quickstart, we’ll use the existing tags file available in the container. Then click **Next**.
+6. Select the container where you’ve uploaded your data. When asked if your files are already tagged with classes, select **Yes** and choose the available file. Then click **Next**.
 
 7. Review the data you entered and select **Create Project**.
 
@@ -100,7 +100,7 @@ After your model is deployed, you can start using it for entity extraction. Use
 
 2. Select the model you want to test.
 
-3. Add your text to the textbox, you can also upload a `.txt` file. 
+3. Using one of the files you downloaded earlier, add the file's text to the textbox. You can also upload a `.txt` file. 
 
 4. Click on **Run the test**.