Instructions to use MVPWendi/wenditraineddelibarate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MVPWendi/wenditraineddelibarate with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MVPWendi/wenditraineddelibarate", 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
- Draw Things
- DiffusionBee
- Xet hash:
- a38399ba0bd39424ce70f1bb7b03143f62c23ff62a228f51e45e76c773189aff
- Size of remote file:
- 246 MB
- SHA256:
- eab3523a800aa4acaa14f80ebd12968a85d95b3a487182a3f06ff614c7089b0b
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