Upload app.py

app.py

@@ -1,5 +1,6 @@
 import streamlit as st
 from transformers import pipeline
+from transformers import AutoModelForQuestionAnswering, AutoTokenizer
 
 st.set_page_config(page_title="Automated Question Answering System")
 st.title("Automated Question Answering System")
@@ -8,7 +9,9 @@ st.subheader("Try")
 @st.cache_resource(show_spinner=True)
 def question_model():
     model_name = "deepset/roberta-base-squad2"
-    question_answerer = pipeline(model=model_name, tokenizer=model_name, task="question-answering")
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForQuestionAnswering.from_pretrained(model_name)
+    question_answerer = pipeline("question-answering", model=model, tokenizer=tokenizer)
     return question_answerer
 
 st.markdown("<h2 style='text-align: center; color:grey;'>Question Answering on Academic Essays</h2>", unsafe_allow_html=True)
@@ -33,7 +36,7 @@ with tab1:
             answer = question_answerer(context=context, question=question)
             answer = answer["answer"]
             container = st.container(border=True)
-            container.write("<h5><b>Answer:</b></h5><hr>" + answer, unsafe_allow_html=True)
+            container.write("<h5><b>Answer:</b></h5>" + answer, unsafe_allow_html=True)
                         
 with tab2:
     uploaded_file = st.file_uploader("Choose a .txt file to upload", type=["txt"])