Instructions to use ilkerzgi/krea-2-aged-wetplate-monochrome-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ilkerzgi/krea-2-aged-wetplate-monochrome-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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ilkerzgi/krea-2-aged-wetplate-monochrome-lora") prompt = "a lighthouse on a rocky cliff. aged wetplate monochrome style" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- af20706680b3f108fe2f688475cc2ce0bf8cb24ca9fee1ca89c3f18d82ac64d6
- Size of remote file:
- 235 MB
- SHA256:
- 36c987aafc5085352e37aba0ff8c1eb22a273cf9ae3312c2159968f8334da82d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.