Instructions to use ACE-Step/acestep-transcriber with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ACE-Step/acestep-transcriber with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("ACE-Step/acestep-transcriber") model = AutoModelForTextToWaveform.from_pretrained("ACE-Step/acestep-transcriber") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 620c659f40f76f80d30ec52fd55f5292f2b9c70e9b9e316bf68e9a06c3de9136
- Size of remote file:
- 4.99 GB
- SHA256:
- 071da93822e38312d02622100832b984fc8623fe864be63fb43b5a43074eed10
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