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XonarLabs/OLOID_Framework
OLOID_Framework is a text-to-image model from XonarLabs. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as apache-2.0.
Downloads · 30 days
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From the Hugging Face model README
OLOID Framework is an open-source LoRA framework for automotive design generation.
Built on Flux.1 dev, it is designed for agent retrieval and invocation, aiming to hand over the tedious parameter-tuning process in design gacha (LoRA stacking + seed sampling) workflows to agents and free up designers’ time.
It also supports manual combination and use by designers.
The current release includes 49 LoRAs, organized across four dimensions and designed to be combined based on different design goals.
For example: PRD (define volume) + CRT (add form language) + INS (expand creative possibilities) + VIS (control visual output)
| Dimension | Code | Role |
|---|---|---|
| Production | PRD | Production-oriented volume, proportion, and structural foundation |
| Creative | CRT | Advances form language and design variation |
| Inspiration | INS | Introduces cross-domain design language and additional stimulus |
| Visuals | VIS | Controls image style, material feel, and overall visual impression |
A full structural overview is shown below:
Figure: Full structure across PRD / CRT / INS / VIS and EXT / INT / PART.
For each LoRA’s trigger words, reference prompts, and recommended weights, please refer to the index:
The current phase of OLOID on Flux.1 has been completed. We have already moved on to exploring next-generation model training and a more complete agent-oriented workflow, so this generation will no longer be updated.
Feedback and testing are welcome.
For discussions around AI generation systems for automotive design, please contact OkeyDesign: [email protected]
For custom training, agent-related and other technical topics, please contact XonarLabs: [email protected]
This model is built on FLUX.1 dev.
Usage may be subject to the base model's license restrictions.
OkeyDesign & XonarLabs