Instructions to use k2styles/krea-2-luminous-crystalline-bokeh-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use k2styles/krea-2-luminous-crystalline-bokeh-lora 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("k2styles/krea-2-luminous-crystalline-bokeh-lora") prompt = "a child flying a kite. luminous crystalline bokeh style" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 73b285f8cb8759f083eda104028b405258d46577597160627aeac948a2412ccc
- Size of remote file:
- 469 MB
- SHA256:
- e8a687226a40e501de24514e708cfa84b1002db7b95d6143385c650174e5bb9c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.