Update README.md

README.md

@@ -119,11 +119,15 @@ SMaLL-100 is a compact and fast massively multilingual machine translation model
 
 The model architecture and config are the same as [M2M-100](https://huggingface.co/facebook/m2m100_418M/tree/main) implementation, but the tokenizer is modified to adjust language codes. So, you should load the tokenizer locally from [tokenization_small100.py](https://huggingface.co/alirezamsh/small100/blob/main/tokenization_small100.py) file for the moment.
 
-**Note**: SMALL100Tokenizer requires sentencepiece, so make sure to install it by ```pip install sentencepiece```
+**Note**: SMALL100Tokenizer requires sentencepiece, so make sure to install it by:
+
+```pip install sentencepiece```
 
 - **Supervised Training**
 
-SMaLL-100 is a seq-to-seq model for the translation task. The input to the model is ```source:[tgt_lang_code] + src_tokens + [EOS]``` and ```target: tgt_tokens + [EOS]```. An example of supervised training is shown below:
+SMaLL-100 is a seq-to-seq model for the translation task. The input to the model is ```source:[tgt_lang_code] + src_tokens + [EOS]``` and ```target: tgt_tokens + [EOS]```. 
+
+An example of supervised training is shown below:
 
 ```
 from transformers import M2M100ForConditionalGeneration