Instructions to use FlyingRoastDuck/I_DRUID with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FlyingRoastDuck/I_DRUID with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FlyingRoastDuck/I_DRUID", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8fa46ede89f63522917624dd741186e13588d31fee22c58c44f970b529ef851
- Size of remote file:
- 10 GB
- SHA256:
- d2e0ae19e5e70480ff363aa1a93a0a131709fd39ce96add223426e22ef82e655
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