| from transformers import pipeline | |
| import gradio as gr | |
| # Load model (this runs once) | |
| generator = pipeline("text-generation", model="gpt2") | |
| # Function for UI | |
| def generate_text(prompt): | |
| results = generator( | |
| prompt, | |
| max_length=25, | |
| num_return_sequences=2, | |
| do_sample=True, | |
| temperature=0.7 | |
| ) | |
| # Format output | |
| output = "" | |
| for i, res in enumerate(results): | |
| output += f"Result {i+1}:\n{res['generated_text']}\n\n" | |
| return output | |
| # Gradio UI | |
| interface = gr.Interface( | |
| fn=generate_text, | |
| inputs="text", | |
| outputs="text", | |
| title="Text Generator", | |
| description="Enter a prompt to generate text" | |
| ) | |
| interface.launch() |