apple/ml-mdm
Train high-quality text-to-image diffusion models in a data & compute efficient manner
Based on the README, here's a technical summary: Implements Matryoshka Diffusion Models, a multi-scale architecture that trains a single pixel-space diffusion model across resolutions (64x to 1024x1024) by progressively expanding the model hierarchy, enabling efficient high-resolution synthesis. Built on U-Net and nested U-Net implementations with DDPM diffusion pipelines, configured via dataclass-based SimpleParsing for flexible model/dataset composition. Provides pretrained checkpoints trained on 50M Flickr pairs and CC12M, with inference via web UI and modular training scripts supporting distributed training.
515 stars and 7 monthly downloads. No commits in the last 6 months. Available on PyPI.
Stars
515
Forks
36
Language
Python
License
MIT
Category
Last pushed
Mar 27, 2025
Monthly downloads
7
Commits (30d)
0
Dependencies
1
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/apple/ml-mdm"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related models
huggingface/diffusers
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
bghira/SimpleTuner
A general fine-tuning kit geared toward image/video/audio diffusion models.
mcmonkeyprojects/SwarmUI
SwarmUI (formerly StableSwarmUI), A Modular Stable Diffusion Web-User-Interface, with an...
nateraw/stable-diffusion-videos
Create 🔥 videos with Stable Diffusion by exploring the latent space and morphing between text prompts
probabilists/azula
Diffusion models in PyTorch