Instructions to use ACE-Step/ACE-Step-v1-3.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ACE-Step/ACE-Step-v1-3.5B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ACE-Step/ACE-Step-v1-3.5B", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - ACE-Step
How to use ACE-Step/ACE-Step-v1-3.5B with ACE-Step:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Thanks.. Really..
#9
by ZiggyS - opened
Just a thanks for putting this out, and lowering the VRAM requirements ( for those of us with 2 medium GPUs, instead of 1 large GPU.. works great with stuff like llama.cpp since it can share, but not so much for diffusion stuff )
its really putting out some great stuff.. looking forward to extending the time a tad.. had one last night "man, this is GREAT.. oh noooo..... it ended....nooooooo "