Create .sample

.sample

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+from diffusers import StableDiffusionImg2ImgPipeline
+import torch
+from PIL import Image
+
+# Load the pipeline
+pipe = StableDiffusionImg2ImgPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", torch_dtype=torch.float16)
+pipe = pipe.to("cuda")  # Use "cuda" if you have a GPU; otherwise, use "cpu"
+
+# Load the input image
+init_image = Image.open("path/to/your/image.jpg").convert("RGB")
+
+# Define the prompt for transformation
+prompt = "A futuristic cityscape at sunset, with neon lights and high-tech buildings"
+
+# Run the image-to-image pipeline
+output = pipe(prompt=prompt, init_image=init_image, strength=0.75, guidance_scale=7.5)
+
+# Save the result
+output.images[0].save("path/to/save/transformed_image.jpg")