fix changes

openfl-workspace/torch_cnn_mnist/README.md

@@ -122,43 +122,6 @@ class MNISTDataset(ImageFolder):
 ```
 Use a pre-sharded version of the standard MNIST dataset (divided among two data owners). The pre-sharded dataset can be downloaded from [mnist_data_shards.tar.gz](https://github.com/securefederatedai/openfl-contrib/blob/main/openfl_contrib_tutorials/ml_to_fl/federated/mnist_data_shards.tar.gz). 
 
-Copy the dataset bundle to the root of the FL workspace and unpack it:
-```
-cp mnist_data_shards.tar.gz ~/openfl/openfl-workspace/torch_cnn_mnist/
-cd ~/openfl/openfl-workspace/torch_cnn_mnist/
-tar -xvf mnist_data_shards.tar.gz
-rm mnist_data_shards.tar.gz
-```
-This will populate the data folder of the FL workspace with two shards (data/1 and data/2) of labeled MNIST images of digits (the 0–9 labels being encoded in the sub-folder names). 
-```
-data
-├── 1
-    └── mnist_images
-        └── 0
-        └── 1
-        └── 2
-        └── 3
-        └── 4
-        └── 5
-        └── 6
-        └── 7
-        └── 8
-        └── 9
-├── 2
-    └── mnist_images
-        └── 0
-        └── 1
-        └── 2
-        └── 3
-        └── 4
-        └── 5
-        └── 6
-        └── 7
-        └── 8
-        └── 9
-```
-Use a pre-sharded version of the standard MNIST dataset (divided among two data owners). The pre-sharded dataset can be downloaded from [mnist_data_shards.tar.gz](https://github.com/securefederatedai/openfl-contrib/blob/main/openfl_contrib_tutorials/ml_to_fl/federated/mnist_data_shards.tar.gz). 
-
 Copy the dataset bundle to the root of the FL workspace and unpack it:
 ```
 cp mnist_data_shards.tar.gz ~/openfl-quickstart/fl_workspace
@@ -211,7 +174,7 @@ fx plan initialize --input_shape [1,28,28] --aggregator_address localhost
 We can now perform a test run with the following commands for creating a local PKI setup and starting the aggregator and the collaborators on the same machine:
 
 ```
-cd ~/openfl/openfl-workspace/torch_cnn_mnist/
+cd ~/openfl-quickstart/fl_workspace
 
 # This will create a local certificate authority (CA), so the participants communicate over a secure TLS Channel
 fx workspace certify