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:
- 22a8d97299c0a08624c10b0fa75b64b79c1d343f6c8f236d342a7bd959a4e072
- Size of remote file:
- 1.37 MB
- SHA256:
- a934a71afed7ab42b3dd6a83a5b6e6d155e19a8ffa98ad74519c44dc6e0cd436
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