Update README.md

README.md

@@ -20,8 +20,8 @@ tokenizer = PegasusTokenizer.from_pretrained(model_name)
 model = PegasusForConditionalGeneration.from_pretrained(model_name).to(torch_device)
 
 def get_response(input_text,num_return_sequences,num_beams):
-  batch = tokenizer([input_text],truncation=True,padding='longest',max_length=60, return_tensors="pt").to(torch_device)
-  translated = model.generate(**batch,max_length=60,num_beams=num_beams, num_return_sequences=num_return_sequences, temperature=1.5)
+  batch = tokenizer([input_text],truncation=True,padding='longest',max_length=2500, return_tensors="pt").to(torch_device)
+  translated = model.generate(**batch,max_length=2500,num_beams=num_beams, num_return_sequences=num_return_sequences, temperature=1.5)
   tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)
   return tgt_text
 ```