Instructions to use ostris/krea2_turbo_style_reference with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ostris/krea2_turbo_style_reference 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("ostris/krea2_turbo_style_reference") prompt = "a white yeti with horns reading a book that is titled \"Ostris + Krea2 Style Reference\"" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
Browse files
README.md
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@@ -54,6 +54,32 @@ This LoRA will allow you to inference on the Krea2 Turbo model in the style of a
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For inference in Comfy UI you will need this custom node. [ComfyUI-Krea2-Ostris-Edit](https://github.com/ostris/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.
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For inference in Comfy UI you will need this custom node. [ComfyUI-Krea2-Ostris-Edit](https://github.com/ostris/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.
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For diffusers, there is a communiuty pipeline here [ostris/Krea2OstrisEdit](https://huggingface.co/ostris/Krea2OstrisEdit). You can run it like below:
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```python
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import torch
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from diffusers import DiffusionPipeline
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from PIL import Image
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pipe = DiffusionPipeline.from_pretrained(
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"krea/Krea-2-Turbo",
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custom_pipeline="ostris/Krea2OstrisEdit",
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torch_dtype=torch.bfloat16,
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)
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pipe.enable_model_cpu_offload() # or pipe.to("cuda") with ~40+ GB of VRAM
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# An AI-Toolkit Krea 2 LoRA, e.g. the style reference LoRA
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pipe.load_lora_weights(
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"ostris/krea2_turbo_style_reference", weight_name="krea2_style_reference.safetensors"
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)
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image = pipe(
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"a white yeti with horns reading a book",
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image=Image.open("style_reference.png"), # one reference image or a list of them
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).images[0]
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image.save("output.png")
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```
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