Instructions to use DeverStyle/Krea2-Loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DeverStyle/Krea2-Loras 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("DeverStyle/Krea2-Loras") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
NotFal

- Prompt
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Model description
A repository to show how bad the recently uploaded Fal Krea2 loras really can be and why you should not copy their training parameters or ever call a lora trained on 8 images a style lora.
Two models are available just for your comparison pleasure, use the trigger word n0t_f4l for both.
- a
n0t_f4l_000001000(1000 steps / LR 0.0001) and a fal versionn0t_f4l_bad_100(100 steps / LR 0.00035).
Download model
Download them in the Files & versions tab.
- Downloads last month
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