Instructions to use hf-internal-testing/tiny-random-BarkModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BarkModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="hf-internal-testing/tiny-random-BarkModel")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-BarkModel") model = AutoModelForTextToWaveform.from_pretrained("hf-internal-testing/tiny-random-BarkModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86006a0c5a39a6aa1f4a1a7fee6ec108b95d90b51b51b4ec72f4cf73f0cb9612
- Size of remote file:
- 937 kB
- SHA256:
- 42ab778f9e3cb38c721b7b702eb9c4a1d635297521bfa4d10ac23eb8ca12c5be
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