Instructions to use madebyollin/taesdxl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use madebyollin/taesdxl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("madebyollin/taesdxl", 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
- Xet hash:
- 58980621ca1a9def2717fc0ff9636ca5877664af636af8af0fee636c5cdae71f
- Size of remote file:
- 4.9 MB
- SHA256:
- f6013131e7eb412ef20113f1acc2ea7d3e47e53196ca0530fa65d9b61d814b61
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