Instructions to use voidful/hubert-tiny-100-pr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/hubert-tiny-100-pr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="voidful/hubert-tiny-100-pr")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("voidful/hubert-tiny-100-pr") model = AutoModelForCTC.from_pretrained("voidful/hubert-tiny-100-pr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 582318348d6621fee1d64ed0ccb31d0a048014a90a499fc13cbfaadc2a27ca8d
- Size of remote file:
- 66 MB
- SHA256:
- 7d3057bf3e040633f41bde63051e88fe27410e720e3980187e9f6a20cc7e217d
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