Instructions to use DeverStyle/Krea-2-Premium-Loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DeverStyle/Krea-2-Premium-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-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("DeverStyle/Krea-2-Premium-Loras") prompt = "Style transfer samples" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- aa4855a187ed436f0d42c4e9257d87a11037d511363fed5dc7e93032f5c20241
- Size of remote file:
- 4.26 MB
- SHA256:
- 8cc7001c3194df6f7d5dcacadfb6cf09a8444afa40789c44134e118a1e67c8e4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.