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:
- 7e67402fafc00931c6e4001dfd0c7326c7ba392bc146b890fabce764ec13476e
- Size of remote file:
- 3.15 GB
- SHA256:
- 9d19d04152d3e261d52d64c1b02cffe6eb0f0e585646ec8982bffd1bf3a57ba8
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