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_8_coarse_prompt.npy from suno/bark-small: direct link, hf CLI and curl.
- Browser
- Download file 7.42 kB
-
https://huggingface.co/suno/bark-small/resolve/main/speaker_embeddings/de_speaker_8_coarse_prompt.npy
- Command line
-
hf download hf://suno/bark-small/speaker_embeddings/de_speaker_8_coarse_prompt.npy
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curl -L -o de_speaker_8_coarse_prompt.npy https://huggingface.co/suno/bark-small/resolve/main/speaker_embeddings/de_speaker_8_coarse_prompt.npy
7.42 kB
- Xet hash:
- 43fefe9d12f113105cd459b1acc16e5668ac80bece76c04a89835dc036ecf7e7
- Size of remote file:
- 7.42 kB
- SHA256:
- 06efd00181d007e30b7b7bede472ea50e9f7c61aa7b76074884d26eec8d965f7
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