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app.py

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+import gradio as gr
+
+import torch
+from torch import autocast
+from diffusers import StableDiffusionPipeline
+from datasets import load_dataset
+from PIL import Image  
+import re
+
+model_id = "CompVis/stable-diffusion-v1-4"
+device = "cuda"
+
+pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=True)
+pipe = pipe.to(device)
+
+def infer(prompt):
+    with autocast("cuda"):
+        images_list = pipe(
+            [prompt])['sample']
+    return images_list
+prompt = 'a perfect photo of a sunset on a Greek beach' 
+
+intf = gr.Interface(fn = infer, inputs = prompt, outputs = gr.outputs.Image())
+
+intf.launch()