Update README.md

README.md

@@ -8,10 +8,13 @@ This model can be used to generate an input caption from a SMILES string.
 ## Example Usage
 ```python
 from transformers import T5Tokenizer, T5ForConditionalGeneration
+
 tokenizer = T5Tokenizer.from_pretrained("laituan245/molt5-small-smiles2caption", model_max_length=512)
 model = T5ForConditionalGeneration.from_pretrained('laituan245/molt5-small-smiles2caption')
+
 input_text = 'C1=CC2=C(C(=C1)[O-])NC(=CC2=O)C(=O)O'
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+
 outputs = model.generate(input_ids, num_beams=5, max_length=512)
 print(tokenizer.decode(outputs[0], skip_special_tokens=True))
 ```