Instructions to use charris/hubert_base_528_10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use charris/hubert_base_528_10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="charris/hubert_base_528_10")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("charris/hubert_base_528_10") model = AutoModelForCTC.from_pretrained("charris/hubert_base_528_10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58d4c3f65e00083fc16c6f8249bab2fbf1e1ddfc98c6bd88bfc594bcbb99b792
- Size of remote file:
- 5.11 kB
- SHA256:
- 954f4cd8ffde40b58b00caede145f96c2fb7bd41d20879bc3e1bab4900c6606f
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