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:
- ea97df66b9df3d233152d966ca386eb7a5d7a8464414c4be3c4881bedc364c81
- Size of remote file:
- 3.58 kB
- SHA256:
- 0381495b54c370e6d38e942bb2ae6473d32d991def1f19929e5743fc082f6697
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