resolve merge conflict

Author: laujan

articles/ai-services/translator/custom-translator/azure-ai-foundry/beginners-guide.md

@@ -139,11 +139,11 @@ To prepare for training, documents undergo a series of processing and filtering
 
 * ### Invalid characters
 
-  custom translation removes sentences that contain Unicode character U+FFFD. The character U+FFFD indicates a failed encoding conversion.
+  Custom translation removes sentences that contain Unicode character U+FFFD. The character U+FFFD indicates a failed encoding conversion.
 
 * ### Invalid HTML tags
 
-  custom translation removes valid tags during training. Invalid tags cause unpredictable results and should be manually removed. 
+  Custom translation removes valid tags during training. Invalid tags cause unpredictable results and should be manually removed. 
 
 ## What steps should I take before uploading data?
 

articles/ai-services/translator/custom-translator/azure-ai-foundry/how-to/create-language-pair.md

@@ -16,7 +16,9 @@ An Azure AI Foundry custom translation language pair includes models, training,
 
 ## Create a language pair
 
-1. Follow [Create a project](create-language-pair.md), then continue here.
+1. Follow [Create a project](create-project.md), then continue here.
+
+1. Use the dropdown list to select another **Connected service** or create a new one.
 
 1. Enter the following details about your language pair in the dialog:
 
@@ -33,13 +35,23 @@ An Azure AI Foundry custom translation language pair includes models, training,
 
    - **Language pair label:** You can add label to create the same language pair multiple times. Example, you want to create English to French model for shopping and another English to French model for automotive. A label distinguishes between the same language pair with the same language pair and domain. As a best practice, here are a few tips:
 
+<<<<<<< HEAD
    - Use a label *only* if you're planning to build multiple projects for the same language pair and same domain and want to access these projects with a different Domain ID.
 
    - Don't use a label if you're building systems for one domain only.
 
    - A label isn't required and not helpful to distinguish between language pairs.
 
    - You can use the same label for multiple language pairs.
+=======
+      - Use a label *only* if you're planning to build multiple projects for the same language pair and same domain and want to access these projects with a different Domain ID.
+
+      - Don't use a label if you're building systems for one domain only.
+
+      - A label isn't required and not helpful to distinguish between language pairs.
+
+      - You can use the same label for multiple language pairs.
+>>>>>>> melghazali/main
 
    - **Project description:** A short summary about the project. This description has no influence over the behavior of the Custom Translator or your resulting custom system, but can help you differentiate between different projects.
 
@@ -55,11 +67,18 @@ To modify the language pair name, description, domain description, and add/remov
 
 1. Select the language pair name from the Fine-tuning > AI Service fine-tuning page.
 
+<<<<<<< HEAD
 1. Select the **...** next to the language pair name and select **Edit**.
 
 1. The **Edit and Delete** buttons should now be visible.
    :::image type="content" source="../media/fine-tune-edit-language-pair-1.png" alt-text="Screenshot illustrating edit language pair fields":::
 
+=======
+   :::image type="content" source="../media/fine-tune-edit-language-pair-1.png" alt-text="Screenshot illustrating edit language pair fields":::
+
+1. Select the **`...`** next to the language pair name. The **Edit and Delete** buttons should now be visible.
+
+>>>>>>> melghazali/main
 1. Select **Edit** and fill in or modify existing text.
 
    :::image type="content" source="../media/fine-tune-edit-language-pair-2.png" alt-text="Screenshot illustrating the edit language pair fields":::

articles/ai-services/translator/custom-translator/azure-ai-foundry/how-to/test-model.md

@@ -33,7 +33,7 @@ A BLEU score is a number between zero and 100. A score of zero indicates a low-q
 
    :::image type="content" source="../media/fine-tune-test-model-2.png" alt-text="Screenshot illustrating the test-model function.":::
 
-1. If results are satisfactory, deploy the model to production, otherwise, iterate by adding more human curated training data until you find a winner model.
+1. If results are satisfactory, deploy the model, otherwise, iterate by adding more human curated training data until you find a winner model.
 
 ## Next steps
 

articles/ai-services/translator/custom-translator/azure-ai-foundry/how-to/train-model.md

@@ -35,11 +35,13 @@ Here are the steps to create a custom translation model:
 
    :::image type="content" source="../media/fine-tune-train-model-2.png" alt-text="Screenshot illustrating train model blade.":::
 
-1. Select the data you want to use for training, for example, `Customer-sample-English-German-Training` and review the training cost associated with the selected number of sentences.
+1. Select the data you want to use for training and review the training cost associated with the selected number of sentences.
 
    :::image type="content" source="../media/fine-tune-train-model-3.png" alt-text="Screenshot depicting a view of the train model blade.":::
 
-1. Select **Train model**.
+1. Select **Next**
+
+1. Review and select **Train model**.
 
    :::image type="content" source="../media/fine-tune-train-model-4.png" alt-text="Screenshot illustrating the train model blade.":::
 

articles/ai-services/translator/custom-translator/azure-ai-foundry/how-to/upload-data.md

@@ -14,21 +14,13 @@ ms.topic: how-to
 
 Document types are associated with the language pair selected when you create a project.
 
-1. Sign-in to [Azure AI Foundry](https://ai.azure.com/). 
-
-1. Select **Fine-tuning** from the left pane.
+1. Follow [Create a language pair](create-language-pair.md), then continue here. 
 
 1. Select the language pair **Name** you want to manage.
 
-1. Select **Manage data** and then select **Add data** and choose the dataset type:
-
-    - Training set
-    - Testing set
-    - Tuning set
-    - Phrase Dictionary
-    - Sentence Dictionary
+   :::image type="content" source="../media/fine-tune-edit-language-pair-1.png" alt-text="Screenshot illustrating edit language pair fields":::
 
-   :::image type="content" source="../media/fine-tune-create-language-pair.png" alt-text="Screenshot illustrating the document upload link.":::
+1. Select **Manage data** and then select **Add data**. 
 
 1. Select dataset type and select your data document format.
 
@@ -46,7 +38,7 @@ You can view history of all document uploads details like document type, upload
 
 1. The upload history tab shows history for the selected language pair.
 
-2. This page shows the status of all of your past uploads. It displays
+1. This page shows the status of all of your past uploads. It displays
     uploads from most recent to least recent. Each upload shows name, status, type, and created on.
 
    :::image type="content" source="../media/fine-tune-upload-history.png" alt-text="Screenshot showing the upload history page.":::

articles/ai-services/translator/custom-translator/azure-ai-foundry/overview.md

@@ -34,7 +34,7 @@ Custom translation provides different features to build custom translation syste
 
 ## Get better translations
 
-Azure AI Translator released [Neural Machine Translation (NMT)](https://www.microsoft.com/translator/blog/2016/11/15/microsoft-translator-launching-neural-network-based-translations-for-all-its-speech-languages/) in 2016. NMT provided major advances in translation quality over the industry-standard [Statistical Machine Translation (SMT)](https://en.wikipedia.org/wiki/Statistical_machine_translation) technology. Because NMT better captures the context of full sentences before translating them, it provides higher quality, more human-sounding, and more fluent translations. [Custom Translator](https://ai.azure.com) provides NMT for your custom models resulting in better translation quality.
+Azure AI Translator released [Neural Machine Translation (NMT)](https://www.microsoft.com/translator/blog/2016/11/15/microsoft-translator-launching-neural-network-based-translations-for-all-its-speech-languages/) in 2016. NMT provided major advances in translation quality over the industry-standard [Statistical Machine Translation (SMT)](https://en.wikipedia.org/wiki/Statistical_machine_translation) technology. Because NMT better captures the context of full sentences before translating them, it provides higher quality, more human-sounding, and more fluent translations. [Custom translation](https://ai.azure.com) provides NMT for your custom models resulting in better translation quality.
 
 Custom translation also accepts data that's parallel at the document level to make data collection and preparation more effective. If users have access to versions of the same content in multiple languages but in separate documents, custom translation is able to automatically match sentences across documents. For a list of supported document format, *see* [Custom translation document formats and naming convention](concepts/document-formats-naming-convention.md).
 

articles/ai-services/translator/custom-translator/release-notes.md

@@ -64,7 +64,7 @@ This page presents the latest feature, improvement, bug fix, and known issue rel
 |English (`en`)|Turkish (`tr`)|
 |English (`en`)|Ukrainian (`uk`)|
 |English (`en`)|Vietnamese (`vi`)|
-|English (`en`)|Chinese Simplified (zh-hans)|
+|English (`en`)|zh-hans|
 |Estonian (`et`)|English (`en`)|
 |Finnish (`fi`)|English (`en`)|
 |French (`fr`)|English (`en`)|