Instructions to use voidful/hubert-tiny-v2-unit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/hubert-tiny-v2-unit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="voidful/hubert-tiny-v2-unit")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("voidful/hubert-tiny-v2-unit") model = AutoModelForCTC.from_pretrained("voidful/hubert-tiny-v2-unit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 399661f3420c06429728f1f40fdd0784d7d42a6ba7987ca24322e40b9185a14b
- Size of remote file:
- 103 MB
- SHA256:
- 143c7306d1aa46e1328fd3427c8949ed60218e5dc5bdf217723e80e3de8d9de7
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