more updates

Author: msakande

articles/machine-learning/concept-model-catalog.md

@@ -59,7 +59,7 @@ Llama family models  | Llama-2-7b <br> Llama-2-7b-chat <br> Llama-2-13b <br> Lla
 Mistral family models | mistralai-Mixtral-8x22B-v0-1 <br> mistralai-Mixtral-8x22B-Instruct-v0-1 <br> mistral-community-Mixtral-8x22B-v0-1 <br> mistralai-Mixtral-8x7B-v01 <br> mistralai-Mistral-7B-Instruct-v0-2 <br> mistralai-Mistral-7B-v01 <br> mistralai-Mixtral-8x7B-Instruct-v01 <br> mistralai-Mistral-7B-Instruct-v01 | Mistral-large (2402) <br> Mistral-large (2407) <br> Mistral-small <br> Mistral-Nemo
 Cohere family models | Not available | Cohere-command-r-plus <br> Cohere-command-r <br> Cohere-embed-v3-english <br> Cohere-embed-v3-multilingual <br> Cohere-rerank-3-english <br> Cohere-rerank-3-multilingual
 JAIS | Not available | jais-30b-chat
-Phi3 family models | Phi-3-mini-4k-Instruct <br> Phi-3-mini-128k-Instruct <br> Phi-3-small-8k-Instruct <br> Phi-3-small-128k-Instruct <br> Phi-3-medium-4k-instruct <br> Phi-3-medium-128k-instruct | Phi-3-mini-4k-Instruct <br> Phi-3-mini-128k-Instruct <br> Phi-3-small-8k-Instruct <br> Phi-3-small-128k-Instruct <br> Phi-3-medium-4k-instruct <br> Phi-3-medium-128k-instruct  
+Phi-3 family models | Phi-3-mini-4k-Instruct <br> Phi-3-mini-128k-Instruct <br> Phi-3-small-8k-Instruct <br> Phi-3-small-128k-Instruct <br> Phi-3-medium-4k-instruct <br> Phi-3-medium-128k-instruct <br> Phi-3-vision-128k-Instruct <br> Phi-3.5-mini-Instruct <br> Phi-3.5-vision-Instruct <br> Phi-3.5-MoE-Instruct | Phi-3-mini-4k-Instruct <br> Phi-3-mini-128k-Instruct <br> Phi-3-small-8k-Instruct <br> Phi-3-small-128k-Instruct <br> Phi-3-medium-4k-instruct <br> Phi-3-medium-128k-instruct <br> <br> Phi-3.5-mini-Instruct  
 Nixtla | Not available | TimeGEN-1
 Other models | Available | Not available
 

articles/machine-learning/how-to-deploy-models-phi-3-5-moe.md

@@ -41,7 +41,7 @@ You can learn more about the models in their respective model card:
 
 ## Prerequisites
 
-To use Phi-3.5 MoE chat model with Azure AI Studio, you need the following prerequisites:
+To use Phi-3.5 MoE chat model with Azure Machine Learning, you need the following prerequisites:
 
 ### A model deployment
 
@@ -52,7 +52,7 @@ Phi-3.5 MoE chat model can be deployed to our self-hosted managed inference solu
 For deployment to a self-hosted managed compute, you must have enough quota in your subscription. If you don't have enough quota available, you can use our temporary quota access by selecting the option **I want to use shared quota and I acknowledge that this endpoint will be deleted in 168 hours.**
 
 > [!div class="nextstepaction"]
-> [Deploy the model to managed compute](../concepts/deployments-overview.md)
+> [Deploy the model to managed compute](concept-model-catalog.md#deploy-models-for-inference-with-managed-compute)
 
 ### The inference package installed
 
@@ -75,7 +75,7 @@ Read more about the [Azure AI inference package and reference](https://aka.ms/az
 In this section, you use the [Azure AI model inference API](https://aka.ms/azureai/modelinference) with a chat completions model for chat.
 
 > [!TIP]
-> The [Azure AI model inference API](https://aka.ms/azureai/modelinference) allows you to talk with most models deployed in Azure AI Studio with the same code and structure, including Phi-3.5 MoE chat model.
+> The [Azure AI model inference API](https://aka.ms/azureai/modelinference) allows you to talk with most models deployed in Azure Machine Learning studio with the same code and structure, including Phi-3.5 MoE chat model.
 
 ### Create a client to consume the model
 
@@ -216,7 +216,7 @@ print_stream(result)
 
 #### Explore more parameters supported by the inference client
 
-Explore other parameters that you can specify in the inference client. For a full list of all the supported parameters and their corresponding documentation, see [Azure AI Model Inference API reference](https://aka.ms/azureai/modelinference).
+Explore other parameters that you can specify in the inference client. For a full list of all the supported parameters and their corresponding documentation, see [Azure AI Model Inference API reference](reference-model-inference-api.md).
 
 ```python
 from azure.ai.inference.models import ChatCompletionsResponseFormat
@@ -291,7 +291,7 @@ You can learn more about the models in their respective model card:
 
 ## Prerequisites
 
-To use Phi-3.5 MoE chat model with Azure AI Studio, you need the following prerequisites:
+To use Phi-3.5 MoE chat model with Azure Machine Learning studio, you need the following prerequisites:
 
 ### A model deployment
 
@@ -302,7 +302,7 @@ Phi-3.5 MoE chat model can be deployed to our self-hosted managed inference solu
 For deployment to a self-hosted managed compute, you must have enough quota in your subscription. If you don't have enough quota available, you can use our temporary quota access by selecting the option **I want to use shared quota and I acknowledge that this endpoint will be deleted in 168 hours.**
 
 > [!div class="nextstepaction"]
-> [Deploy the model to managed compute](../concepts/deployments-overview.md)
+> [Deploy the model to managed compute](concept-model-catalog.md#deploy-models-for-inference-with-managed-compute)
 
 ### The inference package installed
 
@@ -323,7 +323,7 @@ npm install @azure-rest/ai-inference
 In this section, you use the [Azure AI model inference API](https://aka.ms/azureai/modelinference) with a chat completions model for chat.
 
 > [!TIP]
-> The [Azure AI model inference API](https://aka.ms/azureai/modelinference) allows you to talk with most models deployed in Azure AI Studio with the same code and structure, including Phi-3.5 MoE chat model.
+> The [Azure AI model inference API](https://aka.ms/azureai/modelinference) allows you to talk with most models deployed in Azure Machine Learning studio with the same code and structure, including Phi-3.5 MoE chat model.
 
 ### Create a client to consume the model
 
@@ -476,7 +476,7 @@ for await (const event of sses) {
 
 #### Explore more parameters supported by the inference client
 
-Explore other parameters that you can specify in the inference client. For a full list of all the supported parameters and their corresponding documentation, see [Azure AI Model Inference API reference](https://aka.ms/azureai/modelinference).
+Explore other parameters that you can specify in the inference client. For a full list of all the supported parameters and their corresponding documentation, see [Azure AI Model Inference API](reference-model-inference-api.md).
 
 ```javascript
 var messages = [
@@ -558,7 +558,7 @@ You can learn more about the models in their respective model card:
 
 ## Prerequisites
 
-To use Phi-3.5 MoE chat model with Azure AI Studio, you need the following prerequisites:
+To use Phi-3.5 MoE chat model with Azure Machine Learning studio, you need the following prerequisites:
 
 ### A model deployment
 
@@ -569,7 +569,7 @@ Phi-3.5 MoE chat model can be deployed to our self-hosted managed inference solu
 For deployment to a self-hosted managed compute, you must have enough quota in your subscription. If you don't have enough quota available, you can use our temporary quota access by selecting the option **I want to use shared quota and I acknowledge that this endpoint will be deleted in 168 hours.**
 
 > [!div class="nextstepaction"]
-> [Deploy the model to managed compute](../concepts/deployments-overview.md)
+> [Deploy the model to managed compute](concept-model-catalog.md#deploy-models-for-inference-with-managed-compute)
 
 ### The inference package installed
 
@@ -613,7 +613,7 @@ using System.Reflection;
 In this section, you use the [Azure AI model inference API](https://aka.ms/azureai/modelinference) with a chat completions model for chat.
 
 > [!TIP]
-> The [Azure AI model inference API](https://aka.ms/azureai/modelinference) allows you to talk with most models deployed in Azure AI Studio with the same code and structure, including Phi-3.5 MoE chat model.
+> The [Azure AI model inference API](https://aka.ms/azureai/modelinference) allows you to talk with most models deployed in Azure Machine Learning studio with the same code and structure, including Phi-3.5 MoE chat model.
 
 ### Create a client to consume the model
 
@@ -758,7 +758,7 @@ StreamMessageAsync(client).GetAwaiter().GetResult();
 
 #### Explore more parameters supported by the inference client
 
-Explore other parameters that you can specify in the inference client. For a full list of all the supported parameters and their corresponding documentation, see [Azure AI Model Inference API reference](https://aka.ms/azureai/modelinference).
+Explore other parameters that you can specify in the inference client. For a full list of all the supported parameters and their corresponding documentation, see [Azure AI Model Inference API](reference-model-inference-api.md).
 
 ```csharp
 requestOptions = new ChatCompletionsOptions()
@@ -837,7 +837,7 @@ You can learn more about the models in their respective model card:
 
 ## Prerequisites
 
-To use Phi-3.5 MoE chat model with Azure AI Studio, you need the following prerequisites:
+To use Phi-3.5 MoE chat model with Azure Machine Learning studio, you need the following prerequisites:
 
 ### A model deployment
 
@@ -848,7 +848,7 @@ Phi-3.5 MoE chat model can be deployed to our self-hosted managed inference solu
 For deployment to a self-hosted managed compute, you must have enough quota in your subscription. If you don't have enough quota available, you can use our temporary quota access by selecting the option **I want to use shared quota and I acknowledge that this endpoint will be deleted in 168 hours.**
 
 > [!div class="nextstepaction"]
-> [Deploy the model to managed compute](../concepts/deployments-overview.md)
+> [Deploy the model to managed compute](concept-model-catalog.md#deploy-models-for-inference-with-managed-compute)
 
 ### A REST client
 
@@ -862,7 +862,7 @@ Models deployed with the [Azure AI model inference API](https://aka.ms/azureai/m
 In this section, you use the [Azure AI model inference API](https://aka.ms/azureai/modelinference) with a chat completions model for chat.
 
 > [!TIP]
-> The [Azure AI model inference API](https://aka.ms/azureai/modelinference) allows you to talk with most models deployed in Azure AI Studio with the same code and structure, including Phi-3.5 MoE chat model.
+> The [Azure AI model inference API](https://aka.ms/azureai/modelinference) allows you to talk with most models deployed in Azure Machine Learning studio with the same code and structure, including Phi-3.5 MoE chat model.
 
 ### Create a client to consume the model
 
@@ -1023,7 +1023,7 @@ The last message in the stream has `finish_reason` set, indicating the reason fo
 
 #### Explore more parameters supported by the inference client
 
-Explore other parameters that you can specify in the inference client. For a full list of all the supported parameters and their corresponding documentation, see [Azure AI Model Inference API reference](https://aka.ms/azureai/modelinference).
+Explore other parameters that you can specify in the inference client. For a full list of all the supported parameters and their corresponding documentation, see [Azure AI Model Inference API](reference-model-inference-api.md).
 
 ```json
 {
@@ -1145,9 +1145,8 @@ It is a good practice to start with a low number of instances and scale up as ne
 
 ## Related content
 
-
-* [Azure AI Model Inference API](../reference/reference-model-inference-api.md)
+* [Azure AI Model Inference API](reference-model-inference-api.md)
 * [Deploy models as serverless APIs](deploy-models-serverless.md)
 * [Consume serverless API endpoints from a different Azure AI Studio project or hub](deploy-models-serverless-connect.md)
 * [Region availability for models in serverless API endpoints](deploy-models-serverless-availability.md)
-* [Plan and manage costs (marketplace)](costs-plan-manage.md#monitor-costs-for-models-offered-through-the-azure-marketplace)
+* [Plan and manage costs (marketplace)](costs-plan-manage.md#monitor-costs-for-models-offered-through-the-azure-marketplace)

articles/machine-learning/how-to-deploy-models-phi-3-5-vision.md

@@ -297,7 +297,7 @@ import IPython.display as Disp
 Disp.Image(requests.get(image_url).content)
 ```
 
-:::image type="content" source="../media/how-to/sdks/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="../media/how-to/sdks/slms-chart-example.jpg":::
+:::image type="content" source="media/how-to-deploy-models-phi-3-5-vision/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="media/how-to-deploy-models-phi-3-5-vision/slms-chart-example.jpg":::
 
 Now, create a chat completion request with the image:
 
@@ -631,7 +631,7 @@ img.src = data_url;
 document.body.appendChild(img);
 ```
 
-:::image type="content" source="../media/how-to/sdks/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="../media/how-to/sdks/slms-chart-example.jpg":::
+:::image type="content" source="media/how-to-deploy-models-phi-3-5-vision/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="media/how-to-deploy-models-phi-3-5-vision/slms-chart-example.jpg":::
 
 Now, create a chat completion request with the image:
 
@@ -979,7 +979,7 @@ string dataUrl = $"data:image/{imageFormat};base64,{imageBase64}";
 
 Visualize the image:
 
-:::image type="content" source="../media/how-to/sdks/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="../media/how-to/sdks/slms-chart-example.jpg":::
+:::image type="content" source="media/how-to-deploy-models-phi-3-5-vision/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="media/how-to-deploy-models-phi-3-5-vision/slms-chart-example.jpg":::
 
 Now, create a chat completion request with the image:
 
@@ -1225,7 +1225,7 @@ The last message in the stream has `finish_reason` set, indicating the reason fo
 
 #### Explore more parameters supported by the inference client
 
-Explore other parameters that you can specify in the inference client. For a full list of all the supported parameters and their corresponding documentation, see [Azure AI Model Inference API reference](https://aka.ms/azureai/modelinference).
+Explore other parameters that you can specify in the inference client. For a full list of all the supported parameters and their corresponding documentation, see [Azure AI Model Inference API reference](reference-model-inference-api.md).
 
 ```json
 {
@@ -1332,11 +1332,11 @@ Phi-3.5-vision-Instruct can reason across text and images and generate text comp
 To see this capability, download an image and encode the information as `base64` string. The resulting data should be inside of a [data URL](https://developer.mozilla.org/en-US/docs/Web/HTTP/Basics_of_HTTP/Data_URLs):
 
 > [!TIP]
-> You will need to construct the data URL using an scripting or programming language. This tutorial use [this sample image](../media/how-to/sdks/slms-chart-example.jpg) in JPEG format. A data URL has a format as follows: `data:image/jpg;base64,0xABCDFGHIJKLMNOPQRSTUVWXYZ...`.
+> You will need to construct the data URL using an scripting or programming language. This tutorial use [this sample image](media/how-to-deploy-models-phi-3-5-vision/slms-chart-example.jpg) in JPEG format. A data URL has a format as follows: `data:image/jpg;base64,0xABCDFGHIJKLMNOPQRSTUVWXYZ...`.
 
 Visualize the image:
 
-:::image type="content" source="../media/how-to/sdks/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="../media/how-to/sdks/slms-chart-example.jpg":::
+:::image type="content" source="media/how-to-deploy-models-phi-3-5-vision/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="media/how-to-deploy-models-phi-3-5-vision/slms-chart-example.jpg":::
 
 Now, create a chat completion request with the image:
 

articles/machine-learning/how-to-deploy-models-phi-3-vision.md

@@ -296,7 +296,7 @@ import IPython.display as Disp
 Disp.Image(requests.get(image_url).content)
 ```
 
-:::image type="content" source="media/how-to-deploy-models-phi-3-visions/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="media/how-to-deploy-models-phi-3-vision/slms-chart-example.jpg":::
+:::image type="content" source="media/how-to-deploy-models-phi-3-vision/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="media/how-to-deploy-models-phi-3-vision/slms-chart-example.jpg":::
 
 Now, create a chat completion request with the image:
 
@@ -630,7 +630,7 @@ img.src = data_url;
 document.body.appendChild(img);
 ```
 
-:::image type="content" source="media/how-to-deploy-models-phi-3-visions/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="media/how-to-deploy-models-phi-3-vision/slms-chart-example.jpg":::
+:::image type="content" source="media/how-to-deploy-models-phi-3-vision/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="media/how-to-deploy-models-phi-3-vision/slms-chart-example.jpg":::
 
 Now, create a chat completion request with the image:
 
@@ -978,7 +978,7 @@ string dataUrl = $"data:image/{imageFormat};base64,{imageBase64}";
 
 Visualize the image:
 
-:::image type="content" source="media/how-to-deploy-models-phi-3-visions/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="media/how-to-deploy-models-phi-3-vision/slms-chart-example.jpg":::
+:::image type="content" source="media/how-to-deploy-models-phi-3-vision/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="media/how-to-deploy-models-phi-3-vision/slms-chart-example.jpg":::
 
 Now, create a chat completion request with the image:
 
@@ -1331,11 +1331,11 @@ Phi-3-vision-128k-Instruct can reason across text and images and generate text c
 To see this capability, download an image and encode the information as `base64` string. The resulting data should be inside of a [data URL](https://developer.mozilla.org/en-US/docs/Web/HTTP/Basics_of_HTTP/Data_URLs):
 
 > [!TIP]
-> You will need to construct the data URL using an scripting or programming language. This tutorial use [this sample image](media/how-to-deploy-models-phi-3-visions/) in JPEG format. A data URL has a format as follows: `data:image/jpg;base64,0xABCDFGHIJKLMNOPQRSTUVWXYZ...`.
+> You will need to construct the data URL using an scripting or programming language. This tutorial use [this sample image](media/how-to-deploy-models-phi-3-vision/) in JPEG format. A data URL has a format as follows: `data:image/jpg;base64,0xABCDFGHIJKLMNOPQRSTUVWXYZ...`.
 
 Visualize the image:
 
-:::image type="content" source="media/how-to-deploy-models-phi-3-visions/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="media/how-to-deploy-models-phi-3-vision/slms-chart-example.jpg":::
+:::image type="content" source="media/how-to-deploy-models-phi-3-vision/slms-chart-example.jpg" alt-text="A chart displaying the relative capabilities between large language models and small language models." lightbox="media/how-to-deploy-models-phi-3-vision/slms-chart-example.jpg":::
 
 Now, create a chat completion request with the image: