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:
- f9d3a394a34b0fb211efa28fb820481d576310696905c3966cb3f4c59eaab7a1
- Size of remote file:
- 3.46 GB
- SHA256:
- 7e5f98d8bc3583186f7f860ac23f37568bc6ad7aecf0ddf961d74905126cd587
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