| from transformers import pipeline | |
| import gradio as gr | |
| # Load the open-source model | |
| generator = pipeline("text-generation", model="gpt2") | |
| # Define a function to interact with the model | |
| def generate_text(prompt): | |
| results = generator(prompt, max_length=50, num_return_sequences=1) | |
| return results[0]['generated_text'] | |
| # Create a Gradio interface | |
| interface = gr.Interface( | |
| fn=generate_text, | |
| inputs="text", | |
| outputs="text", | |
| title="Text Generator" | |
| ) | |
| # Launch the app | |
| interface.launch() | |