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:
- 7f3b959f658c43cb5e69ca60ef3b5d9fa8190ad40e82226953811629fa4a8b05
- Size of remote file:
- 5.98 kB
- SHA256:
- 7be7d81cb55364f3db979ce92315e2e64517203b9300caca6414970ec81c220b
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