Instructions to use fusing/rdm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fusing/rdm with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fusing/rdm", 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:
- d36d9e93ac0d592395e2533306f8c10d5e81793ae4d88fafcc3aa8a9f57e6e31
- Size of remote file:
- 1.71 GB
- SHA256:
- 7728e9b727b59f4a59c62a90e788295c9886722bec92540cc13bc5a0784d7a23
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