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 The notebook for the exercise in Chapter 10 is available from here:
 [Notebook for mini U-net](https://github.com/vedranaa/teaching-notebooks/blob/main/02506_week10_MiniUnet.ipynb)
 
-You can also open it directly in Google Colab from here:
+Training the network may take long time, especially without GPU. We therefore sketch several ways of running the notebook with GPU support.
+
+## Run the notebook on Google Colab
+
+You can open the notebook in Google Colab from here, and enable GPU :
 [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/vedranaa/teaching-notebooks/blob/main/02506_week10_MiniUnet.ipynb)
 
 
 ## Run the notebook on DTU Gbar
 
-It is possible to run the notebook on Gbar on an interactive note. This is done by setting up a Python environment. First you should log onto an interactive GPU node such as `voltash` by running the following command on the command line:
+You can run the notebook on Gbar on an interactive GPU node. 
+
+First get to a terminal on the cluster, either with ssh, ThinLinc client, or a browser-based ThinLinc [thinlinc.gbar.dtu.dk](thinlinc.gbar.dtu.dk). Open the terminal (command line).
+
+Log onto an interactive GPU node such as `voltash` by running the following command on the command line:
 
 `voltash -X`
 
-To set up a Python environment, you can use the script `env02506.sh`. You should place the file `env02506.sh` in a folder on the Gbar and then run the command line:
+To set up a Python environment, you can use the script `env02506.sh` which we provided for you. You should place the file `env02506.sh` in a folder on the Gbar and then run the command:
 
 `source env02506.sh`
 
 The first time you run this, the script will create a new python environment called `env02506` and activate it.
 
-Then you should install the packages needed which include:
+Then you should install the packages:
 
-`pip install torch torchvision`
-
-`pip install Pillow`
-
-`pip install notebook`
+```
+pip install torch torchvision
+pip install Pillow
+pip install notebook
+```
 
 Now you are good to go. You can navigate to the folder that you wish to store the code, download the notebook from the link above, and open a jupyter notebook by typing the following in the command line:
 
 `jupyter-notebook`
+
+## Use QIM platform to access GBar
+
+We are working on establishing an easier way of using Gbar functionality which does the steps described above automatically. This is still experimental.
+
+First go to QIM platform [https://platform.qim.dk/](https://platform.qim.dk/) and log on using your DTU credentials.
+
+Under Tools menu, choose Jupyter launcher. In the new window yype in your DTU credentials (needs to be done twice). Under basic config QIM environment choose `qim3d` (it has the largest number of packages installed). Under advanced config choose HPC queue called `gpuqim`. Tick the checkbox Reset SSH tunnel. Click the button `Start jupyter server`. 
+
+The platform shold launch your job and a button with `Open Jupyter` should appear, leading you to a jupyter server running in your home directory on the Gbar. 
+
+