Instructions to use F16/krea2-turbo-sda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use F16/krea2-turbo-sda with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("F16/krea2-turbo-sda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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README.md
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license_link: https://huggingface.co/krea/Krea-2-Turbo
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base_model: krea/Krea-2-Turbo
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tags:
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# Krea 2 Turbo — SDA Diversity LoRA (v1.0)
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- **Perceptual Flow Matching** — Zhao et al., 2026 ([arXiv:2607.03524](https://arxiv.org/abs/2607.03524)); inspiration for perceptual-space supervision.
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- **[DiffusionOPSD](https://github.com/worldbench/DiffusionOPSD)** (ByteDance / worldbench, 2026) — on-policy self-distillation reference point for this line of work.
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- **[z-image-turbo-sda](https://huggingface.co/F16/z-image-turbo-sda)** (F16, 2026) — the original SDA LoRA lineage on Z-Image-Turbo that this port follows.
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- Core techniques and metrics: [LoRA](https://arxiv.org/abs/2106.09685) (Hu et al., 2022), [CLIP](https://arxiv.org/abs/2103.00020) (Radford et al., 2021), [HPSv2](https://arxiv.org/abs/2306.09341) (Wu et al., 2023).
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license_link: https://huggingface.co/krea/Krea-2-Turbo
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base_model: krea/Krea-2-Turbo
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tags:
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- lora
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- krea2
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- diffusers
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- diversity
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- sda
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- text-to-image
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library_name: diffusers
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---
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# Krea 2 Turbo — SDA Diversity LoRA (v1.0)
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- **Perceptual Flow Matching** — Zhao et al., 2026 ([arXiv:2607.03524](https://arxiv.org/abs/2607.03524)); inspiration for perceptual-space supervision.
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- **[DiffusionOPSD](https://github.com/worldbench/DiffusionOPSD)** (ByteDance / worldbench, 2026) — on-policy self-distillation reference point for this line of work.
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- **[z-image-turbo-sda](https://huggingface.co/F16/z-image-turbo-sda)** (F16, 2026) — the original SDA LoRA lineage on Z-Image-Turbo that this port follows.
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- Core techniques and metrics: [LoRA](https://arxiv.org/abs/2106.09685) (Hu et al., 2022), [CLIP](https://arxiv.org/abs/2103.00020) (Radford et al., 2021), [HPSv2](https://arxiv.org/abs/2306.09341) (Wu et al., 2023).
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