Update app.py

app.py

@@ -1,25 +1,14 @@
 import streamlit as st
 from transformers import T5Tokenizer, T5ForConditionalGeneration
 import torch
-import gdown
 import os
 
-# Function to download and extract the model from Google Drive
-@st.cache_resource
-def download_and_load_model():
-    url = 'https://drive.google.com/uc?id=YOUR_FILE_ID'  # Replace with your actual file ID
-    output = 'T5_samsum.zip'
-    model_path = './T5_samsum'
+# Path to the folder containing the saved model
+model_path = './T5_samsum'
 
-    if not os.path.exists(model_path):
-        gdown.download(url, output, quiet=False)
-        os.system(f"unzip {output} -d {model_path}")
-
-    model = T5ForConditionalGeneration.from_pretrained(model_path)
-    tokenizer = T5Tokenizer.from_pretrained(model_path)
-    return model, tokenizer
-
-model, tokenizer = download_and_load_model()
+# Ensure the model and tokenizer are loaded from the specified folder
+model = T5ForConditionalGeneration.from_pretrained(model_path)
+tokenizer = T5Tokenizer.from_pretrained(model_path)
 
 st.title("T5 Summarization")