| import torch | |
| from diffusers import ShapEPipeline | |
| from diffusers.utils import export_to_gif | |
| # Define checkpoint ID and load pipeline on CPU | |
| ckpt_id = "openai/shap-e" | |
| pipe = ShapEPipeline.from_pretrained(ckpt_id).to("cpu") | |
| # Define generation parameters | |
| guidance_scale = 10.0 # Lowered for efficiency on CPU | |
| num_inference_steps = 32 # Reduced steps for CPU performance | |
| prompt = "a shark" | |
| # Generate images from the prompt with reduced settings | |
| images = pipe( | |
| prompt=prompt, | |
| guidance_scale=guidance_scale, | |
| num_inference_steps=num_inference_steps, | |
| size=256, # Image size for the model | |
| ).images | |
| # Export images to GIF format | |
| gif_path = export_to_gif(images, "shark_3d.gif") | |
| print(f"GIF saved at {gif_path}") | |