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", torch_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:
- f0cae29a93fa2182f026654237a30e428bf639051d16cfb163a2e313140cc5f3
- Size of remote file:
- 167 MB
- SHA256:
- 780931bfb64d8a61384d250aa4b4387f8230da2a3e78bb0561821bd016f500fe
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