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import gradio as gr | |
from optimum.intel.openvino import OVStableDiffusionPipeline | |
from diffusers.training_utils import set_seed | |
quantized_pipe = OVStableDiffusionPipeline.from_pretrained("OpenVINO/Stable-Diffusion-Pokemon-en-quantized", compile=False) | |
quantized_pipe.reshape(batch_size=1, height=512, width=512, num_images_per_prompt=1) | |
quantized_pipe.compile() | |
prompt = "cartoon bird" | |
def generate(image): | |
output = pipe(prompt, num_inference_steps=50, output_type="pil") | |
return output.images[0] | |
gr.Interface( | |
fn=generate, | |
inputs=gr.inputs.Textbox(placeholder="cartoon bird", | |
label="Prompt" | |
"query", | |
lines=1), | |
outputs=gr.outputs.Image(type="auto", label="Generated Image"), | |
title="Quantized stable diffusion", | |
description="", | |
theme="huggingface", | |
).launch() |