Instructions to use hf-tiny-model-private/tiny-random-UniSpeechSatModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-UniSpeechSatModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-UniSpeechSatModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechSatModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechSatModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b743ade3fe037bd6700eaba950fdad8f21fe1ff9117f90b8f5a28e9dc7b952e2
- Size of remote file:
- 132 kB
- SHA256:
- 3e1f18c48d7f50793ceda62c4105bfdca6b6eefaa0cf0e38898881c6de809055
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