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import gradio as gr | |
from diffusers import DiffusionPipeline | |
ldm = DiffusionPipeline.from_pretrained("CompVis/ldm-text2im-large-256") | |
def inference(prompt): | |
images = ldm([prompt], | |
num_inference_steps=15, | |
eta=0.3, | |
guidance_scale=6)["sample"] | |
return images | |
gr.Interface(inference, "text", gr.Gallery()).launch() |