Instructions to use duja1/roy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use duja1/roy with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("duja1/roy", dtype=torch.bfloat16, device_map="cuda") prompt = "r123oy" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 211bcb4d7538d9a5b8e81c432714d63dbf7586bdf9fd2a7f5e31eadb457b47d7
- Size of remote file:
- 2.13 GB
- SHA256:
- 4e4186a8d512ac3aff1066880643c42dcc3f2aa30793125ab54408fbe79b291e
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