Update app.py

app.py

@@ -4,7 +4,7 @@ from transformers import AutoModelWithLMHead, AutoTokenizer
 tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
 model = AutoModelWithLMHead.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
 
-def get_question(answer, context, max_length=64):
+def get_question(context, answer, max_length=64):
   input_text = "answer: %s  context: %s </s>" % (answer, context)
   features = tokenizer([input_text], return_tensors='pt')
 
@@ -12,10 +12,9 @@ def get_question(answer, context, max_length=64):
                attention_mask=features['attention_mask'],
                max_length=max_length)
 
-  return tokenizer.decode(output[0])
+  return tokenizer.decode(output[0])[16:-4]
 
-
-examples = [["The world's first piece of software was written by a computer scientist named Tom Kilburn in 1948.", "1948"], ["The world's first piece of software was written by a computer scientist named Tom Kilburn in 1948.", "Tom Kilburn"]]
+examples = [["The world's first piece of software was written by a computer scientist named Tom Kilburn in 1948.", "1948"], ["The world's first piece of software was written by a computer scientist named Tom Kilburn in 1948.", "Tom Kilburn"], ["The world's first piece of software was written by a computer scientist named Tom Kilburn in 1948.", "computer scientist"]]
 
 demo = gr.Interface(fn=get_question, inputs=["text", "text"], outputs="text", title="Question Generator", examples=examples)
 demo.launch()