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app.py

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+from diffusers import DiffusionPipeline
+
+ldm = DiffusionPipeline.from_pretrained("fusing/latent-diffusion-text2im-large")
+
+generator = torch.manual_seed(42)
+
+prompt = "A painting of a squirrel eating a burger"
+image = ldm([prompt], generator=generator, eta=0.3, guidance_scale=6.0, num_inference_steps=50)
+
+image_processed = image.cpu().permute(0, 2, 3, 1)
+image_processed = image_processed  * 255.
+image_processed = image_processed.numpy().astype(np.uint8)
+image_pil = PIL.Image.fromarray(image_processed[0])
+
+# save image
+image_pil.save("test.png")