AI Notebooks - Fixing Training Rasa tuto link

Author: Y0Coss

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.de-de.md

@@ -14,7 +14,7 @@ routes:
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/de/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/de/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -41,7 +41,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/de/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/de/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -119,7 +119,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/de/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/de/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback
 

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.en-asia.md

@@ -12,7 +12,7 @@ updated: 2023-03-20
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/asia/en/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/asia/en/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -39,7 +39,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/asia/en/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/asia/en/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -117,7 +117,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/asia/en/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/asia/en/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback
 

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.en-au.md

@@ -12,7 +12,7 @@ updated: 2023-03-20
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/au/en/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/au/en/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -39,7 +39,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/au/en/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/au/en/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -117,7 +117,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/au/en/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/au/en/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback
 

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.en-ca.md

@@ -12,7 +12,7 @@ updated: 2023-03-20
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/ca/en/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/ca/en/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -39,7 +39,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/ca/en/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/ca/en/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -117,7 +117,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/ca/en/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/ca/en/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback
 

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.en-ie.md

@@ -12,7 +12,7 @@ updated: 2023-03-20
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/ie/en/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/ie/en/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -39,7 +39,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/ie/en/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/ie/en/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -117,7 +117,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/ie/en/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/ie/en/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback
 

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.en-sg.md

@@ -12,7 +12,7 @@ updated: 2023-03-20
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/sg/en/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/sg/en/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -39,7 +39,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/sg/en/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/sg/en/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -117,7 +117,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/sg/en/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/sg/en/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback
 

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.en-us.md

@@ -12,7 +12,7 @@ updated: 2023-03-20
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/us/en/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/us/en/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -39,7 +39,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/us/en/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/us/en/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -117,7 +117,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/us/en/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/us/en/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback
 

pages/platform/ai/notebook_tuto_10_create_chatbot/guide.es-es.md

@@ -14,7 +14,7 @@ routes:
 
 ## Objective
 
-The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/es/publiccloud/ai/training/train-rasa-chatbot/).
+The aim of the tutorial is to understand how to create and train a chatbot model with AI Notebooks. We will create and train the chatbot with a Visual Studio Code notebook. At the end of the tutorial, we will have a model and we can speak to our chatbot. There is an another tutorial with which you can train your chatbot with the tool `AI Training`: [How to train a chatbot with AI Training](https://docs.ovh.com/es/publiccloud/ai/training/tuto-train-rasa-chatbot/).
 
 We will use the famous open source framework [Rasa](https://rasa.community/) to build the chatbot.
 
@@ -41,7 +41,7 @@ Here is the reference to install the CLI: [CLI Installation](https://docs.ovh.co
 
 The token is now created. Don't forget to save the token to use it later.
 
-Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/es/publiccloud/ai/training/train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
+Now, if you already have trained some Rasa models with AI Training by following [our tutorial](https://docs.ovh.com/es/publiccloud/ai/training/tuto-train-rasa-chatbot/), you already have created a container with your trained models. You can skip the next part and go directly [here](#visualstudiocode).
 
 ### Understand storage concepts
 
@@ -119,7 +119,7 @@ If you want to deploy your created model with the chatbot, you can follow this t
 
 If you want to train a Rasa chatbot with the tool AI Training, please refer to this tutorial:
 
-[How to train a chatbot with docker and AI Training](https://docs.ovh.com/es/publiccloud/ai/training/train-rasa-chatbot/)
+[How to train a chatbot with docker and AI Training](https://docs.ovh.com/es/publiccloud/ai/training/tuto-train-rasa-chatbot/)
 
 ## Feedback