Instructions to use hf-internal-testing/tiny-AceStepPipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-AceStepPipeline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-AceStepPipeline", 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:
- 2f7447427fcb8b78a7630f00124de2262919911db54534aa0de57a49799bbdb7
- Size of remote file:
- 19.5 MB
- SHA256:
- f37932fa44594126f73f925299a6c73e76f6c386d7fc4bce8ec31f9c724710b8
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