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j5155, This is a detailed 3D-printed model of a small, bright yellow boat gently resting on the shoreline of a tropical Caribbean beach. Viewed from a slightly angled side perspective, the boat showcases its rectangular cabin, compact smokestack, gracefully curved hull, and subtle square recess near the stern. Fine layer lines from the 3D printing process are visible, giving the model an authentic feel, complemented by crisp edges and realistic minor imperfections. Soft waves of crystal-clear turquoise water gently touch the boat, creating subtle ripples along the white sandy beach. Bright sunlight illuminates the boat's vivid yellow color, harmoniously contrasting against the serene tropical background featuring lush palm trees, distant islands, and a clear blue sky dotted with delicate clouds, evoking a relaxing, inviting atmosphere7.50.030None4210241import torch
2from diffusers import DiffusionPipeline
3
4model_id = 'stabilityai/stable-diffusion-3.5-large'
5adapter_id = 'AngelZeur/benchy-sd3-dreambooth'
6pipeline = DiffusionPipeline.from_pretrained(model_id)
7pipeline.load_lora_weights(adapter_id)
8
9prompt = "j5155, This is a detailed 3D-printed model of a small, bright yellow boat gently resting on the shoreline of a tropical Caribbean beach. Viewed from a slightly angled side perspective, the boat showcases its rectangular cabin, compact smokestack, gracefully curved hull, and subtle square recess near the stern. Fine layer lines from the 3D printing process are visible, giving the model an authentic feel, complemented by crisp edges and realistic minor imperfections. Soft waves of crystal-clear turquoise water gently touch the boat, creating subtle ripples along the white sandy beach. Bright sunlight illuminates the boat's vivid yellow color, harmoniously contrasting against the serene tropical background featuring lush palm trees, distant islands, and a clear blue sky dotted with delicate clouds, evoking a relaxing, inviting atmosphere"
10negative_prompt = 'blurry, cropped'
11pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
12image = pipeline(
13 prompt=prompt,
14 negative_prompt=negative_prompt,
15 num_inference_steps=30,
16 generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826),
17 width=1024,
18 height=1024,
19 guidance_scale=7.5,
20).images[0]
21image.save("output.png", format="PNG")