Instructions to use kding1/dicoo_model_ddp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kding1/dicoo_model_ddp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kding1/dicoo_model_ddp", 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
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 61311c7638ec9ced46f7c0ca516fb056638077c0f4b1ab86c384e1c2fa6999ef
- Size of remote file:
- 75.9 MB
- SHA256:
- 389b89207b8007d4a5c6329e02c39446cf763bf188b05674829c5db8524980f8
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