fix

Author: santiagxf

articles/ai-studio/how-to/deploy-models-jais.md

@@ -26,9 +26,7 @@ JAIS 30b Chat is an autoregressive bi-lingual LLM for **Arabic** & **English**.
 
 ::: zone pivot="programming-language-python"
 
-## Jais chat models
 
-None
 
 You can learn more about the models in their respective model card:
 
@@ -279,9 +277,7 @@ except HttpResponseError as ex:
 
 ::: zone pivot="programming-language-javascript"
 
-## Jais chat models
 
-None
 
 You can learn more about the models in their respective model card:
 
@@ -553,9 +549,7 @@ catch (error) {
 
 ::: zone pivot="programming-language-csharp"
 
-## Jais chat models
 
-None
 
 You can learn more about the models in their respective model card:
 
@@ -843,9 +837,7 @@ catch (RequestFailedException ex)
 
 ::: zone pivot="programming-language-rest"
 
-## Jais chat models
 
-None
 
 You can learn more about the models in their respective model card:
 

articles/ai-studio/how-to/deploy-models-jamba.md

@@ -25,14 +25,11 @@ The Jamba-Instruct model is AI21's production-grade Mamba-based large language m
 
 ::: zone pivot="programming-language-python"
 
-## Jamba-Instruct chat models
-
-The Jamba Instruct model is AI21's production-grade Mamba-based large language model (LLM) which leverages AI21's hybrid Mamba-Transformer architecture. It's an instruction-tuned version of AI21's hybrid structured state space model (SSM) transformer Jamba model. The Jamba Instruct model is built for reliable commercial use with respect to quality and performance.
 
 
 You can learn more about the models in their respective model card:
 
-* [Jamba-Instruct](https://aka.ms/azureai/landing/Jamba-Instruct)
+* [AI21-Jamba-Instruct](https://aka.ms/azureai/landing/AI21-Jamba-Instruct)
 
 
 ## Prerequisites
@@ -108,7 +105,7 @@ print("Model provider name:", model_info.model_provider)
 ```
 
 ```console
-Model name: Jamba-Instruct
+Model name: AI21-Jamba-Instruct
 Model type: chat-completions
 Model provider name: AI21
 ```
@@ -142,7 +139,7 @@ print("\tCompletion tokens:", response.usage.completion_tokens)
 
 ```console
 Response: As of now, it's estimated that there are about 7,000 languages spoken around the world. However, this number can vary as some languages become extinct and new ones develop. It's also important to note that the number of speakers can greatly vary between languages, with some having millions of speakers and others only a few hundred.
-Model: Jamba-Instruct
+Model: AI21-Jamba-Instruct
 Usage: 
   Prompt tokens: 19
   Total tokens: 91
@@ -279,14 +276,11 @@ except HttpResponseError as ex:
 
 ::: zone pivot="programming-language-javascript"
 
-## Jamba-Instruct chat models
-
-The Jamba Instruct model is AI21's production-grade Mamba-based large language model (LLM) which leverages AI21's hybrid Mamba-Transformer architecture. It's an instruction-tuned version of AI21's hybrid structured state space model (SSM) transformer Jamba model. The Jamba Instruct model is built for reliable commercial use with respect to quality and performance.
 
 
 You can learn more about the models in their respective model card:
 
-* [Jamba-Instruct](https://aka.ms/azureai/landing/Jamba-Instruct)
+* [AI21-Jamba-Instruct](https://aka.ms/azureai/landing/AI21-Jamba-Instruct)
 
 
 ## Prerequisites
@@ -360,7 +354,7 @@ console.log("Model provider name: ", model_info.body.model_provider_name)
 ```
 
 ```console
-Model name: Jamba-Instruct
+Model name: AI21-Jamba-Instruct
 Model type: chat-completions
 Model provider name: AI21
 ```
@@ -400,7 +394,7 @@ console.log("\tCompletion tokens:", response.body.usage.completion_tokens);
 
 ```console
 Response: As of now, it's estimated that there are about 7,000 languages spoken around the world. However, this number can vary as some languages become extinct and new ones develop. It's also important to note that the number of speakers can greatly vary between languages, with some having millions of speakers and others only a few hundred.
-Model: Jamba-Instruct
+Model: AI21-Jamba-Instruct
 Usage: 
   Prompt tokens: 19
   Total tokens: 91
@@ -554,14 +548,11 @@ catch (error) {
 
 ::: zone pivot="programming-language-csharp"
 
-## Jamba-Instruct chat models
-
-The Jamba Instruct model is AI21's production-grade Mamba-based large language model (LLM) which leverages AI21's hybrid Mamba-Transformer architecture. It's an instruction-tuned version of AI21's hybrid structured state space model (SSM) transformer Jamba model. The Jamba Instruct model is built for reliable commercial use with respect to quality and performance.
 
 
 You can learn more about the models in their respective model card:
 
-* [Jamba-Instruct](https://aka.ms/azureai/landing/Jamba-Instruct)
+* [AI21-Jamba-Instruct](https://aka.ms/azureai/landing/AI21-Jamba-Instruct)
 
 
 ## Prerequisites
@@ -654,7 +645,7 @@ Console.WriteLine($"Model provider name: {modelInfo.Value.ModelProviderName}");
 ```
 
 ```console
-Model name: Jamba-Instruct
+Model name: AI21-Jamba-Instruct
 Model type: chat-completions
 Model provider name: AI21
 ```
@@ -689,7 +680,7 @@ Console.WriteLine($"\tCompletion tokens: {response.Value.Usage.CompletionTokens}
 
 ```console
 Response: As of now, it's estimated that there are about 7,000 languages spoken around the world. However, this number can vary as some languages become extinct and new ones develop. It's also important to note that the number of speakers can greatly vary between languages, with some having millions of speakers and others only a few hundred.
-Model: Jamba-Instruct
+Model: AI21-Jamba-Instruct
 Usage: 
   Prompt tokens: 19
   Total tokens: 91
@@ -845,14 +836,11 @@ catch (RequestFailedException ex)
 
 ::: zone pivot="programming-language-rest"
 
-## Jamba-Instruct chat models
-
-The Jamba Instruct model is AI21's production-grade Mamba-based large language model (LLM) which leverages AI21's hybrid Mamba-Transformer architecture. It's an instruction-tuned version of AI21's hybrid structured state space model (SSM) transformer Jamba model. The Jamba Instruct model is built for reliable commercial use with respect to quality and performance.
 
 
 You can learn more about the models in their respective model card:
 
-* [Jamba-Instruct](https://aka.ms/azureai/landing/Jamba-Instruct)
+* [AI21-Jamba-Instruct](https://aka.ms/azureai/landing/AI21-Jamba-Instruct)
 
 
 ## Prerequisites
@@ -904,7 +892,7 @@ The response is as follows:
 
 ```json
 {
-    "model_name": "Jamba-Instruct",
+    "model_name": "AI21-Jamba-Instruct",
     "model_type": "chat-completions",
     "model_provider_name": "AI21"
 }
@@ -937,7 +925,7 @@ The response is as follows, where you can see the model's usage statistics:
     "id": "0a1234b5de6789f01gh2i345j6789klm",
     "object": "chat.completion",
     "created": 1718726686,
-    "model": "Jamba-Instruct",
+    "model": "AI21-Jamba-Instruct",
     "choices": [
         {
             "index": 0,
@@ -994,7 +982,7 @@ You can visualize how streaming generates content:
     "id": "23b54589eba14564ad8a2e6978775a39",
     "object": "chat.completion.chunk",
     "created": 1718726371,
-    "model": "Jamba-Instruct",
+    "model": "AI21-Jamba-Instruct",
     "choices": [
         {
             "index": 0,
@@ -1017,7 +1005,7 @@ The last message in the stream has `finish_reason` set, indicating the reason fo
     "id": "23b54589eba14564ad8a2e6978775a39",
     "object": "chat.completion.chunk",
     "created": 1718726371,
-    "model": "Jamba-Instruct",
+    "model": "AI21-Jamba-Instruct",
     "choices": [
         {
             "index": 0,
@@ -1068,7 +1056,7 @@ Explore other parameters that you can specify in the inference client. For a ful
     "id": "0a1234b5de6789f01gh2i345j6789klm",
     "object": "chat.completion",
     "created": 1718726686,
-    "model": "Jamba-Instruct",
+    "model": "AI21-Jamba-Instruct",
     "choices": [
         {
             "index": 0,

articles/ai-studio/how-to/deploy-models-mistral-nemo.md

@@ -21,8 +21,6 @@ Mistral AI offers two categories of models. Premium models including [Mistral La
 
 ::: zone pivot="programming-language-python"
 
-## Mistral Nemo chat model
-
 Mistral Nemo is a cutting-edge Language Model (LLM) boasting state-of-the-art reasoning, world knowledge, and coding capabilities within its size category.
 
 Mistral Nemo is a 12B model, making it a powerful drop-in replacement for any system using Mistral 7B, which it supersedes. It supports a context length of 128K, and it accepts only text inputs and generates text outputs.
@@ -461,8 +459,6 @@ except HttpResponseError as ex:
 
 ::: zone pivot="programming-language-javascript"
 
-## Mistral Nemo chat model
-
 Mistral Nemo is a cutting-edge Language Model (LLM) boasting state-of-the-art reasoning, world knowledge, and coding capabilities within its size category.
 
 Mistral Nemo is a 12B model, making it a powerful drop-in replacement for any system using Mistral 7B, which it supersedes. It supports a context length of 128K, and it accepts only text inputs and generates text outputs.
@@ -920,8 +916,6 @@ catch (error) {
 
 ::: zone pivot="programming-language-csharp"
 
-## Mistral Nemo chat model
-
 Mistral Nemo is a cutting-edge Language Model (LLM) boasting state-of-the-art reasoning, world knowledge, and coding capabilities within its size category.
 
 Mistral Nemo is a 12B model, making it a powerful drop-in replacement for any system using Mistral 7B, which it supersedes. It supports a context length of 128K, and it accepts only text inputs and generates text outputs.
@@ -1401,8 +1395,6 @@ catch (RequestFailedException ex)
 
 ::: zone pivot="programming-language-rest"
 
-## Mistral Nemo chat model
-
 Mistral Nemo is a cutting-edge Language Model (LLM) boasting state-of-the-art reasoning, world knowledge, and coding capabilities within its size category.
 
 Mistral Nemo is a 12B model, making it a powerful drop-in replacement for any system using Mistral 7B, which it supersedes. It supports a context length of 128K, and it accepts only text inputs and generates text outputs.