| import gradio as gr | |
| from transformers import pipeline | |
| # Use a smaller, publicly available model | |
| model_name = "gpt2" # You can change this to another suitable model | |
| # Create a text generation pipeline | |
| generator = pipeline('text-generation', model=model_name) | |
| def generate_text(prompt): | |
| result = generator(prompt, max_length=100, num_return_sequences=1) | |
| return result[0]['generated_text'] | |
| iface = gr.Interface( | |
| fn=generate_text, | |
| inputs="text", | |
| outputs="text", | |
| title="Text Generation with GPT-2", | |
| description="Enter a prompt to generate text using GPT-2." | |
| ) | |
| iface.launch() |