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:
- 00d028d2ca09b5af2f4b6853434ddffc8b8c47d6e7074aef47c188653c2d01b0
- Size of remote file:
- 67.3 MB
- SHA256:
- cfd9c83a5f3fcfcfc4fd74377c98b5713c7c3a94703634d8b7728b8974d43aa1
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