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/en_speaker_3_coarse_prompt.npy from reach-vb/bark-endpoint: direct link, hf CLI and curl.
- Browser
- Download file 11.3 kB
-
https://huggingface.co/reach-vb/bark-endpoint/resolve/main/speaker_embeddings/en_speaker_3_coarse_prompt.npy
- Command line
-
hf download hf://reach-vb/bark-endpoint/speaker_embeddings/en_speaker_3_coarse_prompt.npy
-
curl -L -o en_speaker_3_coarse_prompt.npy https://huggingface.co/reach-vb/bark-endpoint/resolve/main/speaker_embeddings/en_speaker_3_coarse_prompt.npy
11.3 kB
- Xet hash:
- 681c9c99d8496905d2248d6bbf4463017a0c1021187f6bc606cf7cd55d48f1ba
- Size of remote file:
- 11.3 kB
- SHA256:
- ced32dac3a50fd964373f0f3480a3eadb4c8e59e56139e8bf3eb9ddffc1d4e85
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