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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 2a0a892b16cc23fa3d91ff7811c2b82c99cbc4d114c912d45e8240131ad35e3f
- Size of remote file:
- 492 MB
- SHA256:
- e498be49aeb5b1612998e2fcde70d8eb46603a8df1103d6e707548eab08b9b1c
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