Instructions to use fyhj/cptndat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fyhj/cptndat with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fyhj/cptndat", 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:
- fede92635b59953122fe330d4b77a89f2ca8bf0602854abc6f5420f42b01008a
- Size of remote file:
- 492 MB
- SHA256:
- a26eafb75c061d52c8fe78cad8a74b0a9229bdd9f48b8a2c0d80f7997a4eeffe
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