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:
- a7d0240cac53a4251e2e5feefcd46827ecf09e0c6b900c18c0b1eb78b6ef76e5
- Size of remote file:
- 2.44 GB
- SHA256:
- bc457616e7b14b939e1cbc0de1ec8858a0eabbef0adaf4f5b3021ac55abb1be8
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