Instructions to use VAST-AI/DetailGen3D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VAST-AI/DetailGen3D with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("VAST-AI/DetailGen3D", 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
- Xet hash:
- bb845fda0b740f3c8b1c90f7efec187e13a101c902354517a0b0c6257daf438e
- Size of remote file:
- 971 MB
- SHA256:
- 488d39edc7a7d3cd4d94baea243c4ed583ed830b3b5f0ae781ad6a00aa8d7369
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