Instructions to use Lonuhbow/beth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Lonuhbow/beth 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("Lonuhbow/beth") prompt = "A cinematic portrait of Beth1 as a cyberpunk hacker in a neon-drenched Tokyo alleyway, surrounded by holographic displays." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- fdf3f97b273ffba2fd508727cd371d2c259515d6b5cf4a3bf4cc70d76f3ac4d0
- Size of remote file:
- 1.4 MB
- SHA256:
- dd3a8078e876521a57c8fc4de06ee40af8122c8907eda4dfb340e7b71f1017be
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.