Text-to-Audio
Transformers
Safetensors
ACE-Step
feature-extraction
audio
music
text2music
custom_code
Instructions to use rAVEUK/acestep-v15-xl-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rAVEUK/acestep-v15-xl-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="rAVEUK/acestep-v15-xl-base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rAVEUK/acestep-v15-xl-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1749e9905cb25caa445928249c0f5136b0995e7194c5155d4ffacea7747e4e8d
- Size of remote file:
- 4.99 GB
- SHA256:
- da654de2a66ace691fb06fedca81f14d20451eecd534c04a69d2f0207303ef23
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