Update app.py

app.py

@@ -1,29 +1,12 @@
-# -*- coding: utf-8 -*-
-
-# Importing Dependancies
-
 import gradio as gr
-from transformers import pipeline
-
-"""# Loading Model Name"""
-
-model_name = "deepset/roberta-base-squad2"
-
-"""# Get Predictions
-"""
-
-nlu = pipeline('question-answering', model=model_name, tokenizer=model_name)
-
-def func(context, question):
-  input = {
-      'question':question,
-      'context':context
-  }
-  res = nlu(input)
-  return res["answer", "score"]
-
-descr = "This is a question and Answer Web app, you give it a context and ask it questions based on the context provided"
-
-app = gr.Interface(fn=func, inputs=[gr.inputs.Textbox(lines=3, placeholder="put in your context here..."),"text"], outputs="text", score=score, title="Question Answer App", description=descr)
-
-app.launch()
+description = "Question Answering Demo 🙌🏼"
+title = "Question Answering with Keras"
+context = "Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. See the model here: hf.co/keras-io/transformers-qa"
+question = "What is Keras?"
+interface = gr.Interface.load("huggingface/deepset/xlm-roberta-large-squad2", 
+    description=description,
+    title = title, 
+    theme = "grass",
+    examples = [[context, question]]
+)
+interface.launch()