Update QuestionAnswering.py

QuestionAnswering.py

@@ -3,7 +3,7 @@ import streamlit as st
 import tensorflow as tf
 from transformers import ElectraTokenizerFast, TFElectraForQuestionAnswering
 
-model_hf = 'nguyennghia0902/bestfailed_electra-small-discriminator_5e-05_16'
+model_hf = "nguyennghia0902/bestfailed_electra-small-discriminator_5e-05_16"
 tokenizer = ElectraTokenizerFast.from_pretrained(model_hf)
 reload_model = TFElectraForQuestionAnswering.from_pretrained(model_hf)
 
@@ -27,7 +27,7 @@ def main():
     col1, col2 = st.columns([2, 1])
     col1.title("Question Answering")
 
-    col2.link_button("Explore my model", 'https://huggingface.co/'+model_hf)
+    col2.link_button("Explore my model", "https://huggingface.co/"+model_hf)
 
     question = st.text_area(
         "QUESTION: Please enter a question:",
@@ -42,16 +42,16 @@ def main():
 
     prediction = ""
 
-    upload_file = st.file_uploader("CONTEXT: Or upload a file with some contexts", type=["txt"])
+    upload_file = st.file_uploader("CONTEXT: Or upload a file with some questions", type=["txt"])
     if upload_file is not None:
-        text = upload_file.read().decode("utf-8")
+        question = upload_file.read().decode("utf-8")
 
         for line in text.splitlines():
             line = line.strip()
             if not line:
                 continue
 
-            prediction = predict(question, line)
+            prediction = predict(line, text)
 
             st.success(line + "\n\n" + prediction)