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:
- 1d5550d66f5d6078ec7fb479c37bad7284e6b0848231dbef781c6cfc2893b8da
- Size of remote file:
- 4.99 GB
- SHA256:
- e44b5ec5fa00bb5a0da423355772bfb3688d1330d70ba65cfd5611eebb20f9d5
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