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
what is the usage in front of suno
#13
by Sanchar55 - opened
the quality of the music and the vocals is very bad in front of the suno models and mainly hindi voice are very bad and neither have option for the step edit and many features so making ace step a very weak contender in front of suno
I also just tested this model, i think you need to fine-tune it with a lora to have better quality.
Is there a list of all the available tags and how to better control the result? The documentation is lacking and not maintained, even the workflow is different now on the recent version of ComfyUI.