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:
- ee2455ff57f20929753cb0fc76a7bcb37e84e6990542d048768bf96abc9add12
- Size of remote file:
- 5.35 GB
- SHA256:
- ccdedd35373bc3a16845f1f1452c5c96926f5cbccab01e824f7f15add2c16a35
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