max length set to 200

app.py

@@ -7,12 +7,12 @@ from transformers import pipeline, GPT2Tokenizer, OPTForCausalLM
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 model=OPTForCausalLM.from_pretrained('pushkarraj/opt_paraphraser')
-tokenizer=GPT2Tokenizer.from_pretrained('facebook/opt-1.3b',truncation=True)
+tokenizer=GPT2Tokenizer.from_pretrained('facebook/opt-1.3b',truncation=True,padding=True)
 
 generator=pipeline("text-generation",model=model,tokenizer=tokenizer,device=device)
 
 def cleaned_para(input_sentence):
-  p=generator('<s>'+input_sentence+ '</s>>>>><p>',do_sample=True,max_length=len(input_sentence.split(" "))+512,temperature = 0.9,repetition_penalty=1.2)
+  p=generator('<s>'+input_sentence+ '</s>>>>><p>',do_sample=True,max_length=len(input_sentence.split(" "))+200,temperature = 0.9,repetition_penalty=1.2)
   return p[0]['generated_text'].split('</s>>>>><p>')[1].split('</p>')[0]
 
 from spacy.lang.en import English # updated