Instructions to use Gimbor/cuth123 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Gimbor/cuth123 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("Gimbor/cuth123") prompt = "A futuristic neon-drenched cyberpunk cityscape where a majestic golden lion with holographic wings stalks through the rain, Cuth123, cinematic lighting." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 2005b23d0807bda0c2d0aef284c073148bd815d1ad7fa7100265b619edd8966e
- Size of remote file:
- 1.37 MB
- SHA256:
- 8f351e21aa63efaa5ca512a991a134464ec75b2185f6cdd07683ba16e0966f3a
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