Instructions to use Mitsua/vroid-diffusion-test-unconditional with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Mitsua/vroid-diffusion-test-unconditional with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Mitsua/vroid-diffusion-test-unconditional", 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:
- b3d81a536aac9cca5dadb9117fece31a2afe38bf072bd1ba28180b386b10af2b
- Size of remote file:
- 106 kB
- SHA256:
- 51eb9b9b07ad1568bd51480f78e16ed38cacb366bcd81151e2e567658e389f81
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