huggingface/diffusers
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
Loading star history...
Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
4 releases in the last 90 days, the latest 13 days ago, with 458 contributors on GitHub.
Use Cases & Benefits
- Provides state-of-the-art pretrained diffusion models for generating images, videos, and audio using PyTorch.
- Offers a modular, customizable toolbox with interchangeable schedulers and pipelines for easy inference and training.
- Use for generating high-quality images from text prompts with minimal code using pretrained pipelines.
- Use for building custom diffusion models and schedulers to experiment with novel generative architectures.
- Use for applying text-guided image-to-image transformations, inpainting, and super-resolution tasks.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
🤗 Diffusers is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. Whether you're looking for a simple inference solution or training your own diffusion models, 🤗 Diffusers is a modular toolbox that supports both. Our library is designed with a focus on usability over performance, simple over easy, and customizability over abstractions.
We recommend installing 🤗 Diffusers in a virtual environment from PyPI or Conda. For more details about installing PyTorch, please refer to their official documentation.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
7.5K+229
Open issues
1.6K+206
Compared with peers in Deep Learning
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| rohitg00/ai-engineering-from-scratch | 78.3K | +1.6K | 75 | 1 day ago |
| huggingface/diffusers | 34.9K | — | 64 | 13 days ago |
| SYSTRAN/faster-whisper | 26.5K | — | 40 | 368 days ago |
| GeeeekExplorer/nano-vllm | 16.3K | — | 12 | — |
| Lightning-AI/litgpt | 13.8K | — | 58 | 129 days ago |
| data-privacy-stack/presidio | 11.8K | — | 64 | 10 days ago |
| Category median | 16.3K | — | 58 | — |
Also by huggingface
Other repositories from this maintainer that GStars tracks
- Python168.6K stars
transformers
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
- Python37.3K stars
pytorch-image-models
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
- Python28.7K stars
lerobot
🤗 LeRobot: Making AI for Robotics more accessible with end-to-end learning
- Python22.1K stars
datasets
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
- Rust21.3K stars
candle
Minimalist ML framework for Rust
Discover Repositories
Search across tracked repositories by name or description