Instructions to use hf-tiny-model-private/tiny-random-UniSpeechModel 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-UniSpeechModel 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-UniSpeechModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8b1dfcd869876245502d9f015cabbf0bfacc01148c59de5b3bcb9c57d55bdb2
- Size of remote file:
- 115 kB
- SHA256:
- 86a575dcfa8b52a2efd8d42a705647bb51f236d942811d2523699635d280157a
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