SHI-Labs/Versatile-Diffusion
Versatile Diffusion: Text, Images and Variations All in One Diffusion Model, arXiv 2022 / ICCV 2023 observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1400
- days_rel: n/a
- days_push: 1119
- n_releases_24m: 0
Adoption not part of the score
1334 stars · 84 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Versatile Diffusion is the official PyTorch implementation of a unified multi-flow multimodal diffusion model that handles text-to-image, image-to-text, image-variation, and text-variation in one model. It supports extensions like style-semantics disentanglement, dual-context blending, and latent image editing, with a WebUI and Hugging Face demo.
Use cases
- generate images from text prompts
- generate text captions describing an image
- create variations of an existing image
- blend text and image guidance for generation
- disentangle style and semantics in generated images
- edit images via latent image-to-text-to-image editing
When to choose
- you want one unified model covering multiple text-image generation tasks
- you need research-grade multimodal diffusion with swappable flows
- you want to experiment with dual-guided or disentanglement generation
When to avoid
- you need the latest state-of-the-art image quality from newer diffusion models
- you need video, audio, or 3D generation, which is not yet supported
- you want a lightweight model without GPU resources
Facets
library · maturity maintenance
machine-learning image-processing nlp artificial-intelligence deep-learning image-processing python diffusion-models text-to-image image-to-text multimodal generative-ai stable-diffusion pytorch iccv-2023 natural-language-processing gpu
6 sources
- readme: https://github.com/SHI-Labs/Versatile-Diffusion · fetched 2026-08-28 · 41802b8a3910
- homepage: https://arxiv.org/abs/2211.08332 · fetched 2026-08-29 · 3bffde17aed1
- site_page: https://info.arxiv.org/about/donate.html · fetched 2026-08-29 · cca9c3a11c56
- site_page: https://info.arxiv.org/about/ourmembers.html · fetched 2026-08-29 · 47cbc55ff1de
- site_page: https://info.arxiv.org/about · fetched 2026-08-29 · a1f16f915a9a
- site_page: https://info.arxiv.org/labs/index.html · fetched 2026-08-29 · b14a8d05a0ec
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| SHI-Labs/Versatile-Diffusion | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="SHI-Labs/Versatile-Diffusion")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem