Update app.py

app.py

@@ -1,14 +1,14 @@
-import gradio as gr
 import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM
+import gradio as gr
 
 # Check if GPU is available, otherwise use CPU
-device = "cuda" if torch.cuda.is_available() else "cpu"
+# device = "cuda" if torch.cuda.is_available() else "cpu"
 
 # Load pre-trained GPT-2 model and tokenizer
 model_name = "gpt2-large"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name).to(device)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
 
 def generate_text(input_text, max_length=16, num_beams=5, do_sample=False, no_repeat_ngram_size=2):
@@ -35,7 +35,7 @@ def generate_text(input_text, max_length=16, num_beams=5, do_sample=False, no_re
     return generated_text
 
 
-def generate_text_with_nucleus_search(input_text, max_length=16, do_sample=True, top_p=0.9):
+def generate_text_with_nucleus_search(input_text, max_length=128, do_sample=True, top_p=0.9):
     """
     Generate text with nucleus sampling based on the given input text.
 
@@ -58,14 +58,11 @@ def generate_text_with_nucleus_search(input_text, max_length=16, do_sample=True,
 
 
 # Create Gradio interface
-input_textbox = gr.Textbox(lines=7, label="Input Text", placeholder="Enter your text here...")
-output_textbox = gr.Textbox(label="Generated Text", placeholder="Generated text will appear here...")
+input_text = gr.Textbox(lines=10, label="Input Text", placeholder="Enter text for text generation...")
+output_text = gr.Textbox(label="Generated Text")
 
-gr.Interface(
-    [generate_text, generate_text_with_nucleus_search],
-    inputs=input_textbox,
-    outputs=output_textbox,
-    title="Text Generation with GPT-2",
-    description="Enter some text and generate new text using GPT-2 model.",
-    allow_flagging=False
-).launch(share=True)
+gr.Interface(generate_text, input_text, output_text,
+             title="Text Generation with GPT-2",
+             description="Generate text using the GPT-2 model.",
+             theme="huggingface",
+             allow_flagging="never").launch(share=True)