Update Dataset_Preparation.rst

Author: smasuma98

docs/Machine_Learning_Force_Fields/Dataset_Preparation.rst

@@ -475,13 +475,13 @@ Step 4: Convert All DFT Structures to ML-Ready Format
 
 4. **Pick DFT Structures for Training the Model**
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-Use `consolidate.py` to pick random structures suitable for ML training:
+  Use `consolidate.py` to pick random structures suitable for ML training:
 
-   .. code-block:: bash
+    .. code-block:: bash
 
-      python consolidate.py input.yaml
+        python consolidate.py input.yaml
 
-An example of input YAML file:
+  An example of input YAML file:
 
    .. code-block:: bash
 
@@ -505,13 +505,13 @@ An example of input YAML file:
         periodic: False
         sparse: False
 
-The output files contain:
+  The output files contain:
      * `consolidated_dataset`: a chunk of dataset with the most diverse structures (preferred for ML training).
      * `MD_random_dataset`: random structures picked from MD data.
      * `random_dataset`: random structures from the whole dataset.
 
-Choose the subset preferred for your method and convert according `xyz` file to `npz` using: 
+  Choose the subset preferred for your method and convert according `xyz` file to `npz` using: 
 
-.. code-block:: bash
+  .. code-block:: bash
 
-   xyztonpz.py consolidated_dataset_1000.xyz
+       xyztonpz.py consolidated_dataset_1000.xyz