SavirD/ddpm-unconditional-faces-64x64

Unconditional DDPM for Face Generation

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Built with PyTorch

Hosted on Hugging Face

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Sample Visualizations

Model Generations (Sampling)

Reverse Diffusion Trajectory

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Code to Run Inference

import matplotlib.pyplot as plt
from huggingface_hub import hf_hub_download
import torch

repo_id = "SavirD/ddpm-unconditional-faces-64x64"

hf_hub_download(repo_id=repo_id, filename="model.py", local_dir=".")
hf_hub_download(repo_id=repo_id, filename="pipeline.py", local_dir=".")
weights_path = hf_hub_download(repo_id=repo_id, filename="model_epoch_50.pth")

from pipeline import DDPMFacePipeline

pipeline = DDPMFacePipeline(checkpoint_path=weights_path)
images = pipeline.generate(num_samples=4)

fig, axes = plt.subplots(1, 4, figsize=(12, 3))
for idx, ax in enumerate(axes):
    ax.imshow(images[idx])
    ax.axis('off')
plt.suptitle("Faces via Unconditional DDPM", fontsize=14)
plt.show()