Instructions to use pnparam/hubert1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pnparam/hubert1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="pnparam/hubert1")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("pnparam/hubert1") model = AutoModelForCTC.from_pretrained("pnparam/hubert1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 014418cff19503b8b129b005b6bf028865c839053b3cf2446ad08d3fb4e498c4
- Size of remote file:
- 378 MB
- SHA256:
- cc653ef70b2e114e387438a9438cc77626b0b79edffa59178219a7dcb22ad2d2
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