import gradio as gr
from transformers import GPT2Tokenizer, GPT2LMHeadModel

tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
model = GPT2LMHeadModel.from_pretrained("gpt2")

def generate_text(prompt):
    input_ids = tokenizer.encode(prompt, return_tensors="pt").to('cuda')
    generated_text = model.generate(input_ids, max_length=1024, temperature=0.7, top_k=50, top_p=0.9, do_sample=True, num_return_sequences=1)
    return tokenizer.decode(generated_text.squeeze(), skip_special_tokens=True)

iface = gr.Interface(generate_text, input_type="text", output_type="text", title="GPT-2 Text Generator")
iface.launch()