Instructions to use devarka/karinebisinoto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use devarka/karinebisinoto with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("baidu/ERNIE-Image-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("devarka/karinebisinoto") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 3d0f6d4bfd0c876107708cae6b4097633c04cdcccf0aa7a2b6681454eb4e0472
- Size of remote file:
- 12.4 MB
- SHA256:
- 777e558ff937ce5c4e8ad35a8dac64dc5f2a17cfd24865330375aaa75d712bef
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