Update length

app.py

@@ -11,10 +11,10 @@ qa_model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-base", dev
 def predict(context, intent):
     input_text = "In one word, what is the opposite of: " + intent + "?"
     input_ids = qa_tokenizer(input_text, return_tensors="pt").input_ids
-    opposite_output = qa_tokenizer.decode(qa_model.generate(input_ids, max_length = 1)[0])
+    opposite_output = qa_tokenizer.decode(qa_model.generate(input_ids, max_length=2)[0])
     input_text = "In one word, what is the following describing: " + context
     input_ids = qa_tokenizer(input_text, return_tensors="pt").input_ids
-    object_output = qa_tokenizer.decode(qa_model.generate(input_ids, max_length = 1)[0])
+    object_output = qa_tokenizer.decode(qa_model.generate(input_ids, max_length=2)[0])
     batch = ['I think the ' + object_output + ' are long.', 'I think the ' + object_output + ' are ' + opposite_output, 'I think the ' + object_output + ' are the perfect']
     outputs = []
     for i, hypothesis in enumerate(batch):