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import torch | |
import os | |
auth_token = os.getenv("HF_TOKEN") | |
device = "cuda" if torch.cuda.is_available() else "cpu" | |
torch_dtype = torch.float16 if device == "cuda" else None | |
from diffusers import StableDiffusionPipeline | |
model_id = "CompVis/stable-diffusion-v1-4" | |
pipe = StableDiffusionPipeline.from_pretrained( | |
model_id, use_auth_token=auth_token, revision="fp16", torch_dtype=torch_dtype | |
).to(device) | |
def predict(prompt): | |
return pipe(prompt).images[0] | |
import gradio as gr | |
gradio_ui = gr.Interface( | |
fn=predict, | |
title="Stable Diffusion Demo", | |
description="Enter a description of an image you'd like to generate!", | |
inputs=[ | |
gr.Textbox(lines=2, label="Paste some text here"), | |
], | |
outputs=["image"], | |
examples=[["a photograph of an astronaut riding a horse"]], | |
) | |
gradio_ui.launch() |