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| import gradio as gr | |
| from transformers import pipeline | |
| # Load the text generation pipeline with the GPT-2 model | |
| pipe = pipeline("text-generation", model="openai-community/gpt2") | |
| def generate_text(prompt): | |
| # Generate text using the pipeline | |
| result = pipe(prompt, max_length=100, num_return_sequences=1) | |
| return result[0]['generated_text'] | |
| # Create Gradio interface | |
| title = "GPT-2 Text Generation" | |
| description = "Generate text based on a prompt using the GPT-2 model." | |
| interface = gr.Interface( | |
| fn=generate_text, | |
| inputs=gr.Textbox(label="Enter your prompt"), | |
| outputs=gr.Textbox(label="Generated Text"), | |
| title=title, | |
| description=description, | |
| ) | |
| # Launch the Gradio app | |
| if __name__ == "__main__": | |
| interface.launch() | |