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:
- 4fe92fb306536beb29f502d28574e8cd48f7797f2308d2169a7289496f1ca9ab
- Size of remote file:
- 937 kB
- SHA256:
- 21bc76764d0c21c31e090c3d5c3dcb60bfce2bf8dda8679e46590d91aece068d
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