diff --git a/Chapter10/Readme.md b/Chapter10/Readme.md
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--- a/Chapter10/Readme.md
+++ b/Chapter10/Readme.md
@@ -3,17 +3,23 @@
 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 ssh, ThinLinc client, or 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`
 
@@ -30,3 +36,11 @@ Then you should install the packages needed which include:
 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 
+
+We are working on establishing an easier way of using Gbar functionality which does the steps described above automatically. This is still experimental.
+Go to [https://platform.qim.dk/](https://platform.qim.dk/). Log on. Under Tools start Jupyter launcher. Type in your DTU credentials (it still 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 que 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. 
+
+