Instructions to use voidful/hubert-tiny-unit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/hubert-tiny-unit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="voidful/hubert-tiny-unit")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("voidful/hubert-tiny-unit") model = AutoModelForCTC.from_pretrained("voidful/hubert-tiny-unit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5adb312c0310b7dd184ede159bf76384ec158e5e1c6ddb5569e6cbd35891bf1b
- Size of remote file:
- 135 MB
- SHA256:
- 7c57362cf0ce74cfb5e64f5a75ecfbe92fa6beb9637450a3bb7543c37c00ce2d
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