Update README indentation and space

README.md

@@ -34,6 +34,7 @@ Note that this model is primiarly aimed at predicting whether a Classical Chines
 Note that this model is primiarly aimed at predicting whether a Classical Chinese sentence is a letter title (书信标题) or not.
 
 Here is how to use this model to get the features of a given text in PyTorch:
+
 1. Import model
 ```python
 from transformers import BertTokenizer
@@ -93,8 +94,8 @@ print(f'The predicted probability for the {list(pred_class_proba.keys())[0]} cla
 print(f'The predicted probability for the {list(pred_class_proba.keys())[1]} class: {list(pred_class_proba.values())[1]}')
 >>> The predicted probability for the not-letter class: 0.002029061783105135
 >>> The predicted probability for the letter class: 0.9979709386825562
-pred_class = idx2label[np.argmax(list(pred_class_proba.values()))]
 
+pred_class = idx2label[np.argmax(list(pred_class_proba.values()))]
 print(f'The predicted class is: {pred_class}')
 >>> The predicted class is: letter
 ```