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Image generation
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This LoRA will turn Ideogram 4 into a few step model. It is capable of generating good quality images in as little as 2 steps with no CFG and no unconditional model. It was created with a continuious turbo training method I am working on and still perfecting. I will release more information on that once it is fully polished. This will likely recieve updated versions as the method improves.

Image generation
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This LoRA will allow you to inference on the Krea2 Turbo model in the style of a reference image. It was trained with AI Toolkit using the experimental Krea2 reference image trainer with the turbo training adapter. It was trained on thousands of hand curated style pairs I have been building over the years. It was trained to handle 1-2 reference images. For inference in Comfy UI you will need this custom node. ComfyUI-Krea2-Ostris-Edit Use the template in that repo with this lora for the effect. No trigger word is needed just image and prompt. For diffusers, there is a communiuty pipeline here ostris/Krea2OstrisEdit. You can run it like below:

Image generation
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This is a training adapter designed to be used for fine-tuning krea/Krea-2-Turbo. It was made for use with AI Toolkit but could potentially be used in other trainers as well. If you are implementing it into training code and have questions. I am always happy to help. Just reach out. When you train directly on a step distilled model, the distillation breaks down very quickly. This results in losing the step distillation in an unpredictable way. A de-distill training adapter slows this process down significantly allowing you to do short training runs while preserving the step distillation (speed). You could also train directly on the raw model, but training directly on the turbo model could yield better results. This is really just a hack to significantly slow down the distillation when fine-tuning a distilled model. The distillation will still be broken down over time. What that means is, this adapter will work great for shorter runs such as styles, concepts, and characters. However, doing a long training run will likely lead to the distillation breaking down to a point where artifacts will be produced when the adapter is removed.

Image generation
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This is a de-distilled version of Tongyi-MAI/Z-Image-Turbo. It was fine tuned on images generated by Tongyi-MAI/Z-Image-Turbo in order to break down the turbo distillation. It can be used to train LoRAs on top of that should remain compatability with the base model, or it can be continued to finetune well beyond what you could do with the turbo model with the ostris/zimage_turbo_training_adapter. This can be trained on directly without an adapter. It can also be used for inference directly. For inference, use a low CFG (2.0 - 3.0) and 20-30 steps. It seems to work well with CFG normalization as well.

Image generation
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This is a training adapter designed to be used for fine-tuning Tongyi-MAI/Z-Image-Turbo. It was made for use with AI Toolkit but could potentially be used in other trainers as well. If you are implementing it into training code and have questions. I am always heppy to help. Just reach out. It can also be used as a general de-distillation LoRA for inference to remove the "Turbo" from "Z-Image-Turbo". When you train directly on a step distilled model, the distillation breaks down very quickly. This results in losing the step distillation in an unpredictable way. A de-distill training adapter slows this process down significantly allowing you to do short training runs while preserving the step distillation (speed). This is really just a hack to significantly slow down the distillation when fine-tuning a distilled model. The distillation will still be broken down over time. What that means is, this adapter will work great for shorter runs such as styles, concepts, and characters. However, doing a long training run will likely lead to the distillation breaking down to a point where artifacts will be produced when the adapter is removed.

Image generation
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