Text-to-Audio
Transformers
Diffusers
Safetensors
ACE-Step
feature-extraction
audio
music
text2music
custom_code
Instructions to use ACE-Step/Ace-Step1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ACE-Step/Ace-Step1.5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="ACE-Step/Ace-Step1.5", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ACE-Step/Ace-Step1.5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vae/diffusion_pytorch_model.safetensors from ACE-Step/Ace-Step1.5: direct link, hf CLI and curl.
- Browser
- Download file 337 MB
-
https://huggingface.co/ACE-Step/Ace-Step1.5/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://ACE-Step/Ace-Step1.5/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/ACE-Step/Ace-Step1.5/resolve/main/vae/diffusion_pytorch_model.safetensors
337 MB
- Xet hash:
- e8d754cd5cb69cf864a2d44a61b39bf61354ebac7fc70680bbfdb8ed49b1bc8b
- Size of remote file:
- 337 MB
- SHA256:
- da17edb604c40deaf09e9b24974e590d1ca83a374070e5d0884cfa4bed9a99b0
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