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:
- fbf2ccf9d9f68179eec50c3106c4ba8442ff1b57f4148026db21af54aad425ee
- Size of remote file:
- 168 kB
- SHA256:
- 99c7701e32e92a81ff92c11eed69acb89180faa191aed9d98d622f4cbc4e2d1f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.