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auto3dseg/README.md

@@ -60,13 +60,13 @@ To further demonstrate the capabilities of **Auto3DSeg**, [here](./tasks/instanc
 
 To run Auto3DSeg on your own dataset, you need to build a `datalist.json` file, and pass it to the AutoRunner.
 
-The datalist format is based on the datasets released by the [Medical Segmentation Decathlon](http://medicaldecathlon.com). 
+The datalist format is based on the datasets released by the [Medical Segmentation Decathlon](http://medicaldecathlon.com).
 See the function `load_decathlon_datalist` in `monai/data/decathlon_datalist.py` for a description of the format.
 
 For the AutoRunner, we only need the `training` list in the JSON, it does not use any other fields.
-The `fold` key for each image is not required, as the AutoRunner will automatically create cross-validation folds.  
-If you do add the cross-validation folds beforehand, these should align with the number of folds set in the configuration of the AutoRunner (by default 5, see [notebook](notebooks/auto_runner.ipynb)).  
-Any other metadata, such as `modality`, `numTraining`, `name`, etc. will not be used by the AutoRunner, but we do recommend using metadata fields to keep track of names and versions of your dataset.  
+The `fold` key for each image is not required, as the AutoRunner will automatically create cross-validation folds.
+If you do add the cross-validation folds beforehand, these should align with the number of folds set in the configuration of the AutoRunner (by default 5, see [notebook](notebooks/auto_runner.ipynb)).
+Any other metadata, such as `modality`, `numTraining`, `name`, etc. will not be used by the AutoRunner, but we do recommend using metadata fields to keep track of names and versions of your dataset.
 In short, your `datalist.json` file should look like this:
 
 ```