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:
- 06adf0623f4de21f9648c59967d3c2a20b97173ee2c6a74f686754cf0b460d59
- Size of remote file:
- 2.08 kB
- SHA256:
- a03e84c7f1f4dd97f033d999fea8eb76c4dde6883e1dae67303b6a46bdb57803
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