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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("suno/bark") model = AutoModelForTextToWaveform.from_pretrained("suno/bark", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download speaker_embeddings/de_speaker_8_semantic_prompt.npy from suno/bark: direct link, hf CLI and curl.
- Browser
- Download file 2.56 kB
-
https://huggingface.co/suno/bark/resolve/main/speaker_embeddings/de_speaker_8_semantic_prompt.npy
- Command line
-
hf download hf://suno/bark/speaker_embeddings/de_speaker_8_semantic_prompt.npy
-
curl -L -o de_speaker_8_semantic_prompt.npy https://huggingface.co/suno/bark/resolve/main/speaker_embeddings/de_speaker_8_semantic_prompt.npy
2.56 kB
- Xet hash:
- ddb8ffdd0bc307a2bfa8232d6681bf09ac2cfdc24fd008b6e63b535fa0e4373b
- Size of remote file:
- 2.56 kB
- SHA256:
- 1919388fdd9b0e236e7bdeef4f6ad1416c7b0e49daf72cf5e064b2e2106584aa
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