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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, 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() |