Instructions to use Cooper/breakdomainrealistic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Cooper/breakdomainrealistic with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Cooper/breakdomainrealistic", 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:
- a4327e72d9a27512f210e0393276d54fd834f98c322aae2f8b1e5f330ef88b4f
- Size of remote file:
- 335 MB
- SHA256:
- 1df93fbac7b496846a1cce82e11d7e18b9ad26f0daaa84ec0aa3fc2320437516
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.