Instructions to use suno/bark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suno/bark with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="suno/bark")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("suno/bark") model = AutoModelForTextToWaveform.from_pretrained("suno/bark") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 077ad2776cd619e3dbaab23c574b4ab559d5078dc3d6d08e4bc31d9dcc2041e8
- Size of remote file:
- 3.74 GB
- SHA256:
- 799c87afab4b01537094c63ea231f2c42c9c07aeb16773690540ad251a6d8fab
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