diff --git a/doc.zih.tu-dresden.de/docs/software/distributed_training.md b/doc.zih.tu-dresden.de/docs/software/distributed_training.md
index 4cb32d1da2dca3e124c036c0700ae5f493cf3c2e..05c266d9eef162e9db1f22836faa12a91760e7ee 100644
--- a/doc.zih.tu-dresden.de/docs/software/distributed_training.md
+++ b/doc.zih.tu-dresden.de/docs/software/distributed_training.md
@@ -224,12 +224,12 @@ module load Horovod/0.19.5-fosscuda-2019b-TensorFlow-2.2.0-Python-3.7.4      #Lo
 ```
 
 Or if you want to use Horovod on the Alpha partition you can load it with the dependencies:
+
 ```bash
 module spider Horovod                                               #Check available modules and dependencies
 module load modenv/hiera  GCC/10.2.0  CUDA/11.1.1  OpenMPI/4.0.5 Horovod/0.21.1-TensorFlow-2.4.1
 ```
 
-
 #### Horovod installation
 
 However if it is necessary to use another version of Horovod it is possible to install it manually.
@@ -282,7 +282,8 @@ HOROVOD_GPU_OPERATIONS=NCCL HOROVOD_WITH_TENSORFLOW=1 pip install --no-cache-dir
 horovodrun --check-build
 ```
 
-If you want to use OpenMPI then specify `HOROVOD_GPU_ALLREDUCE=MPI`. To have better performance it is recommended to use NCCL instead of OpenMPI.  
+If you want to use OpenMPI then specify `HOROVOD_GPU_ALLREDUCE=MPI`. 
+To have better performance it is recommended to use NCCL instead of OpenMPI.  
 
 ##### Verify that Horovod works
 
@@ -296,7 +297,6 @@ hvd.rank()
 print('Hello from:', hvd.rank())
 ```
 
-
 #### Example
 
 Horovod is easy to use