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:
- e12c38048615bc02f2808b24df938798fbe55ad8c4a1a0e3a7699923a2af9a38
- Size of remote file:
- 937 kB
- SHA256:
- 608b9b8a20c750e9725c65c5eb062927c9b84a40392c21d1733874227080c7eb
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