Update app.py

app.py

@@ -2,11 +2,6 @@ import streamlit as st
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
 import torch
 
-# Load the pretrained model and tokenizer
-model_name = "distilbert-base-uncased-finetuned-sst-2-english"  # Example model
-model = AutoModelForSequenceClassification.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-
 # Set up the device (GPU or CPU)
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
@@ -34,6 +29,11 @@ def main():
 
     selected_model = st.selectbox("Select a pretrained model", list(model_options.keys()))
 
+    # Load the pretrained model and tokenizer
+    model_name = selected_model
+    model = AutoModelForSequenceClassification.from_pretrained(model_name)
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+
     if st.button("Analyze"):
         sentiment_label, probabilities = perform_sentiment_analysis(text)
         st.write(f"Sentiment: {sentiment_label}")