Update README.md

README.md

@@ -123,7 +123,7 @@ def extract_important_sentences(text):
     paragraph = ' '.join([' '.join(sentence) for sentence in top_sentences])
     return paragraph
 
-def summarize(text, max_tokens, model_type):
+def summarize(text, max_tokens):
 
     config = PeftConfig.from_pretrained(Nevidu/LexBartLo_2)
 
@@ -141,6 +141,8 @@ def summarize(text, max_tokens, model_type):
     outputs = model.generate(input_ids=input_ids, max_new_tokens=max_tokens, do_sample=True, top_p=0.9)
     summary = tokenizer.batch_decode(outputs.detach().cpu().numpy(), skip_special_tokens=True)[0]
     return summary
+
+summary = summarize(text, max_tokens)
 ```
 
 ### Training Procedure