From d0acde6cb8bd802bb9e5fabd33971ebc056250e0 Mon Sep 17 00:00:00 2001
From: Hauke Kirchner <hauke.gronenberg@gwdg.de>
Date: Wed, 21 Aug 2024 12:28:28 +0000
Subject: [PATCH] Update README.md

---
 code/container/README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/code/container/README.md b/code/container/README.md
index c901b51..048b814 100644
--- a/code/container/README.md
+++ b/code/container/README.md
@@ -71,6 +71,8 @@ Below are two examples of how to use HPC JupyterHub. The first example shows the
 5. Stop the JupyterHub server
 	- File -> Hub Control Panel -> Stop My Server 
 
+💎 `cat ~/current.jupyterhub.notebook.log` can give you more details on your JupyterHub sever.
+
 ## Using the container via CLI on the HPC 🏭
 
 The full potential of an HPC cluster can only be utilised using the command line interface (CLI). Workflows can be optimized for the available hardware, such as different accelerators (e.g. GPUs, NPU, ...) and highly parallel workflows. Here a simple workflow using our workshops example is shown, based on the same container, that was used in JupyterHub. For more details please have a look at our [documentation](https://docs.hpc.gwdg.de/index.html), e.g. on [Slurm/GPU Usage](https://docs.hpc.gwdg.de/how_to_use/slurm/gpu_usage/index.html) and [GPU Partitions](https://docs.hpc.gwdg.de/how_to_use/compute_partitions/gpu_partitions/index.html).
-- 
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