Update app.py

app.py

@@ -2,8 +2,10 @@ import torch
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 import streamlit as st
 
-# Load GPT-2 model and tokenizer
+# Model name
 model_name = "YasirAbdali/bart-summarization"
+
+# Load tokenizer and model
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 
@@ -16,9 +18,8 @@ max_length = st.slider("Maximum length of generated text:", min_value=100, max_v
 
 if topic:
     # Construct a detailed prompt
-    prompt = f"""Summarize the following text; {topic}. 
-"""
-
+    prompt = f"Summarize the following text: {topic}"
+    
     # Tokenize input
     input_ids = tokenizer.encode(prompt, return_tensors="pt")
 
@@ -40,10 +41,11 @@ if topic:
     st.subheader("Generated Summary:")
     st.markdown(generated_text)
 
-    # Option to download the blog post
+    # Option to download the summary
     st.download_button(
         label="Download Summary",
         data=generated_text,
         file_name="generated_summary.md",
         mime="text/markdown"
-    )
+    )
+