Update app.py

app.py

@@ -9,7 +9,7 @@ nltk.download('punkt')
 from nltk.tokenize import sent_tokenize
 
 # Define the path to the saved model zip file
-zip_model_path = 'T5_samsum-20240723T171755Z-001.zip'
+zip_model_path = 'bart_model-20240724T051306Z-001.zip'
 
 # Define the directory to extract the model
 model_dir = './model'
@@ -19,7 +19,7 @@ with zipfile.ZipFile(zip_model_path, 'r') as zip_ref:
     zip_ref.extractall(model_dir)
 
 # After unzipping, the model should be in a specific directory, check the directory structure
-model_path = os.path.join(model_dir, 'T5_samsum')
+model_path = os.path.join(model_dir, 'Bart_model')
 
 # Verify that the directory exists and contains the necessary files
 if not os.path.exists(model_path):
@@ -33,7 +33,7 @@ else:
     summarizer = pipeline("summarization", model=model, tokenizer=tokenizer)
 
     # Set the title for the Streamlit app
-    st.title("T5 Summary Generator")
+    st.title("BART Summary Generator")
 
     # Text input for the user
     text = st.text_area("Enter your text: ")