Update app.py

app.py

@@ -7,7 +7,7 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name)
 
 # Streamlit app
-st.title("Blog Post Generator (GPT-2 Large)")
+st.title("blog generator")
 
 # Input area for the topic
 topic = st.text_area("Enter the topic for your blog post:")
@@ -22,10 +22,10 @@ if st.button("Generate Blog Post"):
         inputs_encoded = tokenizer.encode(prompt, return_tensors="pt")
 
         # Generate text
-        model_output = model.generate(inputs_encoded, max_new_tokens=100, do_sample=True, temperature=0.7)
+        model_output = model.generate(inputs_encoded, max_new_tokens=50, do_sample=True, temperature=0.7)
         
         # Decode the output
-        output = tokenizer.decode(model_output, skip_special_tokens=True)
+        output = tokenizer.decode(model_output[0], skip_special_tokens=True)
         
         # Display the generated blog post
         st.subheader("Generated Blog Post:")