Update README.md

README.md

@@ -87,15 +87,14 @@ model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 
-def generate_summary_with_special_tokens(text, max_length=600):
-    inputs = tokenizer(text, return_tensors="pt", max_length=512, truncation=True).to(device)
+def generate_summary_with_special_tokens(text, max_length=512):
+    inputs = tokenizer(text, return_tensors="pt", max_length=max_length, truncation=True).to(device)
     
     outputs = model.generate(
         **inputs,
         max_length=max_length,
         num_return_sequences=1,
         no_repeat_ngram_size=4,
-        # early_stopping=True
     )
     
     generated_text = tokenizer.decode(outputs[0], skip_special_tokens=False)