Instructions to use fyhj/cptndatva with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fyhj/cptndatva 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/cptndatva", 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:
- 6c13a653a0288bfcaf10122b0c93da98bfa1597c3622aa15e8548e28e942eb8c
- Size of remote file:
- 492 MB
- SHA256:
- 31e874e781fe1e31082e64bf12fc3e96d2f4794b049ef4a3690b51f4d82f7e20
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