Update app.py

app.py

@@ -1,7 +1,7 @@
 import streamlit as st
 import numpy as np
 from sentence_transformers import SentenceTransformer
-from transformers import CrossEncoder
+from transformers import pipeline
 
 # Sample passages
 passages = [
@@ -14,7 +14,7 @@ passages = [
 
 # Load models
 embedding_model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
-ranking_model = CrossEncoder('cross-encoder/ms-marco-MiniLM-L-12-v2')
+ranking_model = pipeline("text-classification", model='cross-encoder/ms-marco-MiniLM-L-12-v2')
 
 def get_relevant_passages(question, passages):
     keywords = question.lower().split()