Instructions to use quarterturn/krea2_nichijou with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use quarterturn/krea2_nichijou 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-Raw", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("quarterturn/krea2_nichijou") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
A krea2 bf16 rank 128 style LoRA for making Nichijou images.
Trained on my Nichijou dataset https://huggingface.co/datasets/quarterturn/nichijou-hd-json-captioned.
The dataset was character tagged (to the best of qwen3.6-35b-a3b's ability) so you should be able to make a scene with any main character just by name, though you'll still need to desrcribe their state of dress, since that varies in the actual anime. Checkpoints to step 20000 are provided, which is the final. I think 18500 or later is good.
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Base model
krea/Krea-2-Raw