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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30c50df5d386da84d9bddaa5bb9fc586ae28be358d170c56533bfbf1e0a353ca
- Size of remote file:
- 557 Bytes
- SHA256:
- ddf9b8f9f71c538ea572fa79c3a0c6935fe4a9590a3f4f015b5b1f93a458692b
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