pytorch-stable-diffusion and StableDiffusion-PyTorch

These are competitors—both are educational implementations of Stable Diffusion in PyTorch from scratch, serving the same purpose of teaching the model architecture, with the first offering greater community validation through higher stars.

Maintenance 0/25
Adoption 10/25
Maturity 9/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 9/25
Community 22/25
Stars: 1,037
Forks: 201
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 246
Forks: 56
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About pytorch-stable-diffusion

hkproj/pytorch-stable-diffusion

Stable Diffusion implemented from scratch in PyTorch

Implements the complete diffusion pipeline including text tokenization (via BPE vocabulary), VAE-based latent encoding/decoding, and cross-attention conditioning between text embeddings and image generation. Supports loading pretrained checkpoints from Hugging Face, including fine-tuned models like InkPunk and Illustration Diffusion variants up to v1.5. Designed as an educational reference implementation that faithfully reproduces the original architecture while remaining compatible with the standard model weights ecosystem.

About StableDiffusion-PyTorch

explainingai-code/StableDiffusion-PyTorch

This repo implements a Stable Diffusion model in PyTorch with all the essential components.

Supports multiple conditioning mechanisms—class labels, text (via CLIP embeddings), and semantic masks—either independently or in combination, operating on latent space via VQVAE compression. Uses DDPM with linear scheduling for the diffusion process and provides modular training pipelines for autoencoders and diffusion models across MNIST and CelebHQ datasets, with configuration-driven setup for custom data.

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