Updated the instructions in the README file.

README.md

@@ -19,14 +19,13 @@ The example assumes working experience with Docker.
 > [!IMPORTANT] 
 > For the workshop, we will use PyTorch based compute-package. The workshop leader will provide the dataset and the client configuration file, client.yaml.  
 
-*** For the workshop, we will use PyTorch based compute-package. The workshop leader will provide the dataset and the client configuration file, client.yaml. ***
 
 ### Using Docker (Linux and  MacOS)
 
 Here we assume that the FEDn network is up and running and you have obtained the connection file (client.yaml). In case you are participating in a Scaleout workshop, you will obtain the file from the workshop organizer. If you are working on the tutorial on your own, complete the instructions below before connecting the client.
 
-[!NOTE]
-In case you want to run a client on M1 or M2 macOS using TensorFlow and Keras, make sure you have a compatible framework version.
+> [!NOTE]
+> In case you want to run a client on M1 or M2 macOS using TensorFlow and Keras, make sure you have a compatible framework version.
 
 Clone the repository
 
@@ -37,8 +36,8 @@ cd Power-consumption-tutorial
 
 The following command will connect your client to the FEDn network specified in client.yaml. Please fix the path of the power.npz and client.yaml files according to your local setup.
 
-[!NOTE]
-Make sure that the Docker deamon is running on your system. 
+> [!NOTE]
+> Make sure that the Docker deamon is running on your system. 
 
 ```sh
  docker run -v $PWD/client.yaml:/app/client.yaml -v $PWD/data:/var/data -e ENTRYPOINT_OPTS=--data_path=/var/data/power.npz ghcr.io/scaleoutsystems/power-consumption:pyt_v0.6.0 fedn run client --secure=True --force-ssl -in client.yaml 
@@ -77,8 +76,8 @@ git clone https://github.com/scaleoutsystems/Power-consumption-tutorial.git
 cd Power-consumption-tutorial
 ```
 
-[!NOTE]
-The workshop leader will provide the dataset and the client configuration file, client.yaml.
+> [!NOTE]
+> The workshop leader will provide the dataset and the client configuration file, client.yaml.
 
 Download the 'dataset' and 'client.yaml' file and move them to the 'Power-consumption-tutorial' directory. The directory structure will look as follows:
 
@@ -94,8 +93,8 @@ where the 'data' directory contains the 'power.npz' file.
 
 The following command will connect your client to the FEDn network specified in 'client.yaml'. Please fix the path of the 'power.npz' and 'client.yaml' files according to your local setup.
 
-[!NOTE]
-Make sure that the Docker deamon is running on your system.
+> [!NOTE]
+> Make sure that the Docker deamon is running on your system.
 
 ```sh
 docker run -v $PWD/client.yaml:/app/client.yaml -v $PWD/data:/var/data -e ENTRYPOINT_OPTS=--data_path=/var/data/power.npz ghcr.io/scaleoutsystems/power-consumption:pyt_v0.6.0 fedn run client --secure=True --force-ssl -in client.yaml -in client.yaml