Model Card for Unit 1 of the Diffusion Models Class 🧨
This model is a diffusion model for unconditional image generation of cute 🦋.
Usage
from diffusers import DDPMPipeline
import torch
pipeline = DDPMPipeline.from_pretrained('Chen011/sd-class-butterflies-32').to("cuda" if torch.cuda.is_available() else "cpu")
# Generate random noise
random_noise = torch.randn((1, 3, 64, 64)) # Adjust the shape as per your model's requirements
# Pass through the pipeline
image = pipeline(num_inference_steps=50, generator=torch.manual_seed(42), latents=random_noise).images[0]
image.show()
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This model is not currently available via any of the supported third-party Inference Providers, and
the HF Inference API does not support diffusers models with pipeline type unconditional-image-generation