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:
- 2973f9d0abe736ef2b743f2cfdd5d0ccf2a69212cfd36fefbbf108bab082a5fd
- Size of remote file:
- 2.43 GB
- SHA256:
- 19ac6c0769f8f6a9ffe25540f79d16b8fcb26ac40902c6e5a0ecade50554d635
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