Instructions to use Alex995647/loras-krea-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Alex995647/loras-krea-2 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("Alex995647/loras-krea-2") 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
Add 12 LoRA(s): niji-sweet-spot, detailifier, dark-ghibli-fairytales, grainscape-ultrareal…
a884971 verified - Xet hash:
- 0b2540dca53c3fbbf100637749f8441f3daa6c9d978ef631bb7b23a0ea323330
- Size of remote file:
- 19.7 MB
- SHA256:
- dcc2a90205f11734c26171ebf19d81f0472d3b63323aafda66ed258b2cc23c35
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.