Instructions to use aaronsiim/diffusionai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aaronsiim/diffusionai with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("aaronsiim/diffusionai", 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:
- 76d5d2d69623def9ab3bdd8cf6254c7ae9dcb15c67bf858102b8d0ec5c4ddc15
- Size of remote file:
- 4.27 GB
- SHA256:
- 5f760ae7d97afde97a8b543ffaab9e8b37944ac432e73865435cc95c5e33a860
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