Instructions to use cuongdev/vsvsbsf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/vsvsbsf with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cuongdev/vsvsbsf", 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:
- 3288e141a281e874eda3ded5e6a75aa160d17c4555bb2bb44cab9a603820e7a5
- Size of remote file:
- 681 MB
- SHA256:
- 191d1fac01fa9b804be6bcbbc93d0555b84a19bb19664f9ca024feb33e820965
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