Instructions to use Qilex/VirtualPetDiffusion2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Qilex/VirtualPetDiffusion2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qilex/VirtualPetDiffusion2", 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:
- b7ada5af67db4b42a71e568fe0d6d1e9b2e56f6a993ec182556b045a4b9e3e4b
- Size of remote file:
- 455 MB
- SHA256:
- 26b3adab0088408f8899d50fa9530a01584066ed95d6490025c0e83a92a207ad
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