Instructions to use reach-vb/bark-endpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reach-vb/bark-endpoint with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="reach-vb/bark-endpoint")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("reach-vb/bark-endpoint") model = AutoModelForTextToWaveform.from_pretrained("reach-vb/bark-endpoint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download speaker_embeddings/announcer_coarse_prompt.npy from reach-vb/bark-endpoint: direct link, hf CLI and curl.
- Browser
- Download file 3.13 kB
-
https://huggingface.co/reach-vb/bark-endpoint/resolve/main/speaker_embeddings/announcer_coarse_prompt.npy
- Command line
-
hf download hf://reach-vb/bark-endpoint/speaker_embeddings/announcer_coarse_prompt.npy
-
curl -L -o announcer_coarse_prompt.npy https://huggingface.co/reach-vb/bark-endpoint/resolve/main/speaker_embeddings/announcer_coarse_prompt.npy
3.13 kB
- Xet hash:
- d8d22557b0321166495a08c268125080a64856fffc32618cb9d562a8c4157e9f
- Size of remote file:
- 3.13 kB
- SHA256:
- 2c77d5e1f9ab39e489d27628ab26dfae7a8b4cae4ba72658a1a94927f7ff5132
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