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 text.pt from reach-vb/bark-endpoint: direct link, hf CLI and curl.
- Browser
- Download file 2.32 GB
-
https://huggingface.co/reach-vb/bark-endpoint/resolve/main/text.pt
- Command line
-
hf download hf://reach-vb/bark-endpoint/text.pt
-
curl -L -o text.pt https://huggingface.co/reach-vb/bark-endpoint/resolve/main/text.pt
2.32 GB
- Xet hash:
- 2ef572b61550ad188af7ad6f76409a98521b54d2313a6456492007c47f8f88c7
- Size of remote file:
- 2.32 GB
- SHA256:
- ecd798cf39a5ecbec30ef41a3d9d63fb61ea09b78d3bd5dfebb2f7343087b1be
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