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")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("reach-vb/bark-endpoint") model = AutoModelForTextToWaveform.from_pretrained("reach-vb/bark-endpoint") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e52102841b78cd064c8afdfcbbda56d07150effb225120fc3c27b4b8661e8b21
- Size of remote file:
- 1.11 GB
- SHA256:
- 7ec1eb35cd3e21506b0c045ded225271d9a25d9fa608662585cfd749590a0eac
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