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:
- 8ffcf251024889390ff11c234799ae09dbb63fc3fd4a2eadd083e2b0ada9ea6b
- Size of remote file:
- 9.79 MB
- SHA256:
- ff4824aca94dd6111e0340fa749347fb74101060d9712cb5ef1ca8f1cf17502f
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