Update app.py

app.py

@@ -21,7 +21,7 @@ model_small = AutoModelForSeq2SeqLM.from_pretrained(model_dir_small)
 
 def small(text,model=model_small,tokenizer=tokenizer_small):
     inputs = ["Mask Generation: " + text.lower()+'.']
-    inputs = tokenizer(inputs, max_length=512, truncation=True, return_tensors="pt")
+    inputs = tokenizer(inputs, max_length=256, truncation=True, return_tensors="pt")
     output = model.generate(**inputs, num_beams=8, do_sample=True, max_length=len(text))
     decoded_output = tokenizer.batch_decode(output, skip_special_tokens=True)[0]
     predicted_title = decoded_output.strip()