| import gradio as gr | |
| from transformers import pipeline | |
| # Load pre-trained model and tokenizer | |
| generator = pipeline('text-generation', model='gpt2') | |
| def generate_text(prompt): | |
| response = generator(prompt, max_length=50, num_return_sequences=1) | |
| return response[0]['generated_text'] | |
| interface = gr.Interface(fn=generate_text, inputs="text", outputs="text") | |
| interface.launch() | |