VectorSpaceLab/OmniGen
Some data may be outdated — see provenance labels.
OmniGen: Unified Image Generation. https://arxiv.org/pdf/2409.11340 observed · 2026-10-02
Health v2 · maintenance only
44/100
- Activity 47
- Release rhythm 35
- Longevity 54
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 764
- days_rel: n/a
- days_push: 320
- n_releases_24m: 0
Adoption not part of the score
4346 stars · 364 forks observed · 2026-10-02
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
OmniGen is a unified diffusion-based image generation model that produces and edits images from multi-modal prompts without auxiliary modules like ControlNet or IP-Adapter. The repository provides inference and fine-tuning code, with the model also available via Hugging Face Diffusers and Replicate.
Use cases
- generate images from text prompts
- edit images with natural language instructions
- generate images conditioned on reference images
- do subject-driven generation without extra adapters
- fine-tune an image generation model on custom data
- run unified image generation in Diffusers
When to choose
- you want one model for generation and editing without loading ControlNet or IP-Adapter
- you need multi-modal (text plus image) prompting for image synthesis
- you want a MIT-licensed model you can fine-tune yourself
When to avoid
- you need the absolute highest fidelity from specialized state-of-the-art models like SDXL or Flux
- you have no GPU and need fast cheap inference
- you only need a hosted API with no local setup
Facets
library · maturity active
image-processing machine-learning deep-learning image-processing artificial-intelligence computer-vision python cross-platform diffusion-model text-to-image image-editing multi-modal unified-model diffusers gpu
2 sources
- readme: https://github.com/VectorSpaceLab/OmniGen · fetched 2026-10-02 · ebb0835c829d
- registry_pypi: https://pypi.org/pypi/omnigen/json · fetched 2026-08-29 · f90a5c0d6e7c
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| VectorSpaceLab/OmniGen | main | 44 |
For agents
markdown · JSON · MCP: product_card(name="VectorSpaceLab/OmniGen")
Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem