Instructions to use voidful/hubert-tiny-100-pr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/hubert-tiny-100-pr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="voidful/hubert-tiny-100-pr")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("voidful/hubert-tiny-100-pr") model = AutoModelForCTC.from_pretrained("voidful/hubert-tiny-100-pr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da5076cf8c3c37e0ecf21b99f58c72cf93a35397c92cdbcbd460d772cd2eb92c
- Size of remote file:
- 132 MB
- SHA256:
- 32f4b3c0f5696b4b9f6714bd07e4dc0bdc6b869bd3f2ef24030884e918c0f4cd
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