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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30f6f71c8bdec848950cf58f6f6768fd0f8b42ae065bf52176f167c6fbc45be4
- Size of remote file:
- 2.95 kB
- SHA256:
- 88fee5c6b974dbfb1168b55f73990be270847a91a2e7895d298b188f3ad7da9f
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