Update app.py

app.py

@@ -2,6 +2,7 @@ import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import gradio as gr
 
+
 # Load pre-trained GPT-2 model and tokenizer
 model_name = "gpt2-large"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
@@ -50,9 +51,8 @@ def generate_text_with_nucleus_search(input_text, max_length=16, do_sample=True,
 # Create Gradio input interface
 input_text_interface = gr.Textbox(lines=5, label="Input Text", placeholder="Enter text for generation...")
 
-# Create Gradio output interfaces
+# Create Gradio output interface for regular text generation
 output_text_interface1 = gr.Textbox(label="Generated Text (Regular)", placeholder="Generated text will appear here...")
-output_text_interface2 = gr.Textbox(label="Generated Text (Nucleus Sampling)", placeholder="Generated text will appear here...")
 
 # Interface for regular text generation
 interface1 = gr.Interface(generate_text, input_text_interface, output_text_interface1, 
@@ -60,6 +60,9 @@ interface1 = gr.Interface(generate_text, input_text_interface, output_text_inter
                           description="Generate text using the GPT-2 model with regular generation method.",
                           allow_flagging="never")
 
+# Create Gradio output interface for text generation with nucleus sampling
+output_text_interface2 = gr.Textbox(label="Generated Text (Nucleus Sampling)", placeholder="Generated text will appear here...")
+
 # Interface for text generation with nucleus sampling
 interface2 = gr.Interface(generate_text_with_nucleus_search, input_text_interface, output_text_interface2, 
                           title="Text Generation with Nucleus Sampling",