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:
- 24aa4d99fa20228ac6954ab3ec9c1a6fc3460f88a6ddad9b32a3a1b843afcb43
- Size of remote file:
- 937 kB
- SHA256:
- cd5b0b68b2d4a2a92a03896e8b307ad3b323d1fd8c5d04a5183547d5a45ccd54
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