Updated app.py with pretrained model

app.py

@@ -4,14 +4,14 @@ import gradio as gr
 
 nlp = pipeline('question-answering', model='deepset/roberta-base-squad2', tokenizer='deepset/roberta-base-squad2')
 
-def qnamodel(ques,content):
-  question_set = {'question':ques,'context':content}
+def qnamodel(question,content):
+  question_set = {'question':question,'context':content}
   results = nlp(question_set)
   return results['answer']
 
 interface = gr.Interface(fn=qnamodel, 
                         inputs=["text","text"],
-                         outputs="text", 
+                        outputs="text", 
                         title='Context Question Answering')
                         
 interface.launch(inline=False)