Update app.py

app.py

@@ -8,16 +8,18 @@ from transformers import AutoTokenizer
 # Initializing the pipeline for the question answering model
 question_answerer = pipeline("question-answering", model="Only-Mike/ADHD_Test_qa_model")
 
-gr.Markdown('''ADHD QA Bot <br>
+def question_answer(question, context):
+    # Answering from the trained model
+    result = question_answerer(question=question, context=context)
+    return result["answer"]
+
+gr.Interface(fn=question_answer, inputs=["text", "text"], outputs=["text"]).launch()
+
+gr.Markdown('ADHD QA Bot <br>
 This space is build to showcase a fine-tuning of the distilbert-base-uncased and its abilities to answer questions. <br>
 Examples could be: <br>
 - Question = What is ADHD? <br>
 - Context = Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity.<br>
-''')
+')
 
-def question_answer(question, context):
-    # Answering from the trained model
-    result = question_answerer(question=question, context=context)
-    return result["answer"]
 
-gr.Interface(fn=question_answer, inputs=["text", "text"], outputs=["text"]).launch()