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")# pip install -U transformers accelerate # 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
Download speaker_embeddings/de_speaker_0_coarse_prompt.npy from suno/bark-small: direct link, hf CLI and curl.
- Browser
- Download file 9.47 kB
-
https://huggingface.co/suno/bark-small/resolve/main/speaker_embeddings/de_speaker_0_coarse_prompt.npy
- Command line
-
hf download hf://suno/bark-small/speaker_embeddings/de_speaker_0_coarse_prompt.npy
-
curl -L -o de_speaker_0_coarse_prompt.npy https://huggingface.co/suno/bark-small/resolve/main/speaker_embeddings/de_speaker_0_coarse_prompt.npy
9.47 kB
- Xet hash:
- df6915d7ee68b47971a3249b3e5676607489e22ca8c94fad616339f8ca2f866b
- Size of remote file:
- 9.47 kB
- SHA256:
- 3eb78af32779b5fabbb92e7cdbdeaaa34f5f8ad1085e213b101165665c5ce4cb
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