Instructions to use madebyollin/taesd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use madebyollin/taesd 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/taesd", 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:
- 4f0fbee2d1ef9357eaf4f10903745dabdd6b0f5e16924011c2789a4a16150e66
- Size of remote file:
- 4.9 MB
- SHA256:
- f0fb51dd10d41c26612c070fa0b52ea0215a5ff90792134b4971109dd713c019
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