Instructions to use suno/bark-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suno/bark-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="suno/bark-small")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("suno/bark-small") model = AutoModelForTextToWaveform.from_pretrained("suno/bark-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 83ab828b27da35a72665e5f45f231f3a668821c2bb79dd23ea9b9fbff5c6de23
- Size of remote file:
- 8.61 kB
- SHA256:
- bf0fb48dd18c79996fc800abbd3407dd967b21a36bda695584e29d302ead274a
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