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:
- 14377984bf1cbe0fea804ba125fca8f5575d7fdb55424ca594f8698e41bd25f7
- Size of remote file:
- 1.22 GB
- SHA256:
- 399fba97a95f22c36834418bc69373364a99af3a1153da1c0fb31db567c92e23
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