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:
- 3fff2838ef73e5cd026f45976d0e63b159217d1f6af8e0b01be07d62dba39dd8
- Size of remote file:
- 44.4 kB
- SHA256:
- d0c85765b00ad1c1d19fba17bdc182eca2ebd95b60209da63d485548bc871461
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