Update app.py

app.py

@@ -44,30 +44,26 @@ def fetch_answers(question, document ):
      
     return top_5_query_paragraph_answer_list
 
-
-st.title('Document Question Answering System')
-query = st.text_area("Query", "", height=25)
-document = st.text_area("Document Text", "", height=100)
-st.text("Progress Bar")
+st.text("Loading the models...")
 my_bar = st.progress(0)
-my_bar.progress(10)
-
 model_name = "MaRiOrOsSi/t5-base-finetuned-question-answering"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelWithLMHead.from_pretrained(model_name)
-    
-my_bar.progress(25)
-    
+model = AutoModelWithLMHead.from_pretrained(model_name)    
+my_bar.progress(25)    
 sentence_segmenter = pysbd.Segmenter(language='en',clean=False)
-passage_retreival_model = CrossEncoder('cross-encoder/ms-marco-MiniLM-L-6-v2')
 my_bar.progress(50)
-qa_model = pipeline("question-answering",'a-ware/bart-squadv2')
-  
+passage_retreival_model = CrossEncoder('cross-encoder/ms-marco-MiniLM-L-6-v2')
 my_bar.progress(75)
+qa_model = pipeline("question-answering",'a-ware/bart-squadv2')  
+my_bar.progress(100)
+st.text('Models Loaded')
+
+st.title('Document Question Answering System')
+query = st.text_area("Query", "", height=25)
+document = st.text_area("Document Text", "", height=100)
 
 if st.button("Get Answers From Document"):
     
     st.markdown(fetch_answers(query, document))
-    my_bar.progress(100)