Update app.py

app.py

@@ -15,10 +15,6 @@ import time
 from torch.utils.data import DataLoader, RandomSampler, SequentialSampler
 
 model_checkpoint = "akdeniz27/roberta-base-cuad"
-st.sidebar.write("Model: akdeniz27/roberta-base-cuad")
-st.sidebar.write("Project: https://www.atticusprojectai.org/cuad")
-st.sidebar.write("Git Hub: https://github.com/TheAtticusProject/cuad")
-st.sidebar.write("CUAD Dataset: https://huggingface.co/datasets/cuad")
 
 @st.cache(allow_output_mutation=True)
 def run_prediction(question_texts, context_text, model_path):
@@ -131,10 +127,9 @@ questions = load_questions()
 contracts = load_contracts()
 contract = contracts[0]
 
-st.header("Contract Understanding Atticus Dataset (CUAD) Demo")
-st.write("Based on https://github.com/marshmellow77/cuad-demo")
+st.header("Question Answering in CUAD (Contract Understanding Atticus Dataset)")
 
-selected_question = st.selectbox('Choose one of the 41 queries from the CUAD dataset:', questions)
+selected_question = st.selectbox('Choose one of the queries from the CUAD dataset:', questions)
 question_set = [questions[0], selected_question]
 contract_type = st.radio("Select Contract", ("Sample Contract", "New Contract"))
 
@@ -151,3 +146,10 @@ if Run_Button == True and not len(contract)==0 and not len(question_set)==0:
 	
 	for i, p in enumerate(predictions):
 		if i != 0: st.write(f"Question: {question_set[int(p)]}\n\nAnswer: {predictions[p]}\n\n")
+
+
+st.write("Model: akdeniz27/roberta-base-cuad")
+st.write("Project: https://www.atticusprojectai.org/cuad")
+st.write("Git Hub: https://github.com/TheAtticusProject/cuad")
+st.write("CUAD Dataset: https://huggingface.co/datasets/cuad")
+st.write("Based on https://github.com/marshmellow77/cuad-demo")