Instructions to use Runware/acestep-v15-base-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Runware/acestep-v15-base-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Runware/acestep-v15-base-diffusers", 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:
- 50e3c282187ba05fed66edb58ffbba6f4ce258bd2d3dcda860b8dc125e041bab
- Size of remote file:
- 1.19 GB
- SHA256:
- 0437e45c94563b09e13cb7a64478fc406947a93cb34a7e05870fc8dcd48e23fd
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