make qa work

app.py

@@ -3,9 +3,15 @@ from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
 title = "Vacancy Keyword Extraction"
 description = "Add a vacancy and ask what keyword you would like to retrieve. For example, What is the job title? What is the city? What is the start date?"
 
-gr.Interface.load("huggingface/deepset/roberta-base-squad2", 
+
+classifier = pipeline("question-answering", model="deepset/roberta-base-squad2", model_max_length=512)
+
+def zeroShotClassification(text_input, question):
+    prediction = classifier(context=text_input, question=question, truncation=True, max_length="max_length", padding=True)
+    return f'{prediction["answer"]}'
+
+gr.Interface(fn=zeroShotClassification,
                   inputs=[gr.inputs.Textbox(lines=10, label="Vacancy", placeholder="Paste the context of a vacancy."),
                           gr.inputs.Textbox(lines=2, label="Question", placeholder="Ask what you want to retrieve from the vacancy.")],
-                  outputs=[gr.outputs.Textbox(label="Answer"), 
-                          gr.outputs.Label(label="Probability")],                  
+                  outputs=gr.outputs.Textbox(label="Answer"),
                   title=title, description=description).launch(share=False)

requirements.txt

@@ -1,2 +1,3 @@
 transformers
 gradio
+torch