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:
- ee63665535f4ea3f13c44d274b1b3923ce81027c0c81c82a3eaff597e172e963
- Size of remote file:
- 9.82 MB
- SHA256:
- 1625815ec7e8c3b63a9fa045fe00be825ed7cdf1691a04f24130a69ac057a70e
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