Instructions to use dde/autLi8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dde/autLi8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dde/autLi8", 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:
- 079365ba1d2d29734729fc13b6d9d0911a6848363cc3db3193b4d7b7e2e21283
- Size of remote file:
- 492 MB
- SHA256:
- 475d3b1504545b461f58328128dd07317e6e4ea3887fabf5ff986484f41b8de9
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