Omnico/Krea2_turbo_diff_loras
text-to-image model by Omnico
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Model card & documentation
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These LoRAs were extracted from fine-tuned checkpoints. I did this primarily for myself because LoRAs are easier to work with: they can be mixed in real time and assigned different weights/strengths. This also saves space on your local computer. They work well at 100–150% strength. Choose a rank according to your taste and your hardware capabilities (the lower the rank, the less memory you need). However, some of my test generations showed that a lower rank can sometimes be preferable: it does not…
Read the full model card ↗ · Preview checked 2026-10-28T04:29:56.653Z
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Model overview
Omnico/Krea2_turbo_diff_loras is a text-to-image model repository published by Omnico on Hugging Face. The source reports the diffusers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-to-image
- Library
- diffusers
- Recent downloads (30 days)
- 73,118
- Cumulative likes
- 81
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- Not reported — check the model card
- Access
- Not gated by Hugging Face
- Created
- 2026-08-01T13:23:43.000Z
- Last modified
- 2026-10-18T23:13:13.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: krea/Krea-2-Turbo
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-28T06:48:52.160Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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