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:
- 532dc0cd59f05ccef419e22b8bf0a47e015807258be6c575f9ca901f52d6728f
- Size of remote file:
- 1.27 MB
- SHA256:
- 6e4f1098064bd7efe88fd3a3a203e6ad75a1f6df2d7e5ec4be34f5c968d369b8
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