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app.py

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+import torch
+
+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, 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()