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import gradio as gr | |
from transformers import pipeline | |
# Load the text generation model | |
generator = pipeline("text-generation", model="gpt2", max_length=100) | |
def generate_description(topic): | |
# Prompt the model to describe the topic | |
prompt = f"Describe the following topic briefly: {topic}" | |
result = generator(prompt, max_length=100, num_return_sequences=1) | |
return result[0]["generated_text"] | |
# Create Gradio interface | |
interface = gr.Interface( | |
fn=generate_description, | |
inputs=gr.Textbox(label="Enter a Topic", placeholder="e.g., Heart"), | |
outputs=gr.Textbox(label="Description"), | |
title="Topic Describer", | |
description="Enter a topic, and the app will describe it briefly." | |
) | |
# Launch the app | |
interface.launch() |