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/announcer_semantic_prompt.npy from suno/bark-small: direct link, hf CLI and curl.
- Browser
- Download file 1.13 kB
-
https://huggingface.co/suno/bark-small/resolve/main/speaker_embeddings/announcer_semantic_prompt.npy
- Command line
-
hf download hf://suno/bark-small/speaker_embeddings/announcer_semantic_prompt.npy
-
curl -L -o announcer_semantic_prompt.npy https://huggingface.co/suno/bark-small/resolve/main/speaker_embeddings/announcer_semantic_prompt.npy
1.13 kB
- Xet hash:
- 5bc6ebfe47d02365459a073bcf738c3db0e61e57bbda01873f839d0f2950c0bd
- Size of remote file:
- 1.13 kB
- SHA256:
- f5564642cbd84db6f4d1d8a522bd26329b4f4cd8cd81e1965b90baf1ee80c7ff
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