Create app.py

app.py

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+import torch
+import gradio as gr
+from PIL import image
+import spaces
+from diffusers import StableCascadeDecoderPipeline, StableCascadePriorPipeline
+
+device = "cuda"
+num_images_per_prompt = 1
+
+prior = StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", torch_dtype=torch.bfloat16).to(device)
+decoder = StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade",  torch_dtype=torch.float16).to(device)
+
+prompt = "Anthropomorphic cat dressed as a pilot"
+negative_prompt = ""
+
+@spaces.GPU
+def gen(prompt, negative, width, height):
+    prior_output = prior(
+        prompt=prompt,
+        height=height,
+        width=width,
+        negative_prompt=negative,
+        guidance_scale=4.0,
+        num_images_per_prompt=num_images_per_prompt,
+        num_inference_steps=20
+    )
+    decoder_output = decoder(
+        image_embeddings=prior_output.image_embeddings.half(),
+        prompt=prompt,
+        negative_prompt=negative,
+        guidance_scale=0.0,
+        output_type="pil",
+        num_inference_steps=10
+    ).images
+    return decoder_output
+
+i