Update app.py

app.py

@@ -2,7 +2,7 @@ import streamlit as st
 import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
-# Load GPT-2 model and tokenizer
+# Load GPT-2 large model and tokenizer
 @st.cache(allow_output_mutation=True)
 def load_model():
     tokenizer = AutoTokenizer.from_pretrained("gpt2-large")
@@ -12,7 +12,7 @@ def load_model():
 tokenizer, model = load_model()
 
 st.title("Blog Post Generator")
-st.write("Generate a blog post for a given topic using GPT-2.")
+st.write("Generate a blog post for a given topic using GPT-2 Large.")
 
 # User input for the blog post topic
 topic = st.text_input("Enter the topic for your blog post:")
@@ -24,7 +24,7 @@ if st.button("Generate Blog Post"):
         input_text = f"Write a blog post about {topic}."
         inputs = tokenizer.encode(input_text, return_tensors="pt")
 
-        # Generate the blog post using GPT-2
+        # Generate the blog post using GPT-2 large
         outputs = model.generate(inputs, max_length=500, num_return_sequences=1, no_repeat_ngram_size=2, early_stopping=True)
 
         # Decode the generated text
@@ -35,4 +35,3 @@ if st.button("Generate Blog Post"):
     else:
         st.write("Please enter a topic to generate a blog post.")
 
-