# How to run a template

**Step 1:** Open the project that you would like to work on.

**Step 2:** Scroll down to Data Science Workbench.\
\
**Step 3(Optional):** Toggle the Accelerate Jupyter to assign a GPU to Jupyter. This toggle is optional for regular scripts, it is required for the Jupyter notebooks that involve using models. The tutorial notebooks which require GPUs will state that requirement in the first cell of the notebook. The toggle will be in progress until the GPU is successfully assigned to Jupyter, if there are no available GPUs the request will become queued and catch the next GPU that is freed up. 

![How to accelerate Jupyter if you need to use models ](/files/IASSqj8p2M5SapATaCOj)

![After accelerating Jupyter you will see an in progess state until the GPU is assigned](/files/5ouxryzIaoarFUQr24sn)

**Step 4:** Click on the Jupyter logo, this will open the Jupyter server for this project in a new tab.

![](/files/q8Vrozmz7vifT1zQ2frO)

**Step 5:** Open the tutorial folder and select a template.

**Step 6:** Modify the parameters in the first cell to suit your needs.

**Step 7:** Wait until the circle in the top right corner says Kernel is ready.

**Step 8:** Click the play button to execute the selected cell.

**Step 9:** Observe the output.

**Step 10:** Execute all the cells that you are interested in.

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