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import gradio as gr | |
from diffusers import DiffusionPipeline | |
# Load the pretrained model | |
pipeline = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo") | |
# Define a function to use the model for prediction | |
def predict(text_input): | |
# Use the pipeline to make predictions | |
output = pipeline(text_input) | |
return output | |
# Create a Gradio interface | |
iface = gr.Interface( | |
fn=predict, | |
inputs=gr.Textbox(lines=5, label="Input Text"), | |
outputs=gr.Image(type="numpy", label="Output Image"), | |
title="Diffusion Pipeline App", | |
description="Enter the text to get the model's predictions as an output image." | |
) | |
# Launch the Gradio interface | |
iface.launch() | |