Create app.py

app.py

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+os.system("pip install gradio==3.11")
+os.system("pip install transformers")
+os.system("pip install torch")
+
+import requests
+import gradio as gr
+import os
+
+
+
+from transformers import pipeline
+
+qa_model = pipeline("question-answering")
+
+
+
+def question(context,question):
+    output = qa_model(question = question, context = context)
+    return output['answer']
+    
+demo = gr.Interface(
+    fn=question,
+    inputs=[gr.Textbox(lines=8, placeholder="context Here..."), gr.Textbox(lines=2, placeholder="question Here...")],
+    outputs="text",title="Question answering app",
+    description="This is a question answering app, it can prove useful when you want to extract an information from a large text. All you need to do is copy and paste the text you want to query and then query it with a relevant question",
+    examples=[
+        ["My name is Oluwafunbi Adeneye and I attended Federal University of Agriculture Abeokuta", "What is the name of Oluwafunbi's school?"],
+        ["Cocoa house is the tallest building in Ibadan","what is the name of the tallest building in Ibadan?"],
+    ],
+)
+demo.launch()