Fix model.

app.py

@@ -4,8 +4,15 @@ import streamlit as st
 import socket
 import threading
 
+# Specify the model name explicitly to avoid warnings
+model_name = "distilbert-base-uncased-finetuned-sst-2-english"
+
 # Load the pre-trained sentiment-analysis pipeline
-classifier = pipeline('sentiment-analysis')
+try:
+    classifier = pipeline('sentiment-analysis', model=model_name)
+except Exception as e:
+    st.error(f"Error loading pipeline: {e}")
+    st.stop()
 
 # Function to classify sentiment
 def classify_text(text):