Instructions to use GraydientPlatformAPI/jibmixreal9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GraydientPlatformAPI/jibmixreal9 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("GraydientPlatformAPI/jibmixreal9", 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:
- 8587ee1a86d9341896520bb6f214a8ed33a932760b48a5ca5d113a349d77baf6
- Size of remote file:
- 1.39 GB
- SHA256:
- 6ad1e86180452018c046e20c7c3b327733f10d130370af9187d9eaca13423786
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