Instructions to use rohitp1/libri-alpha-1-Temp-1-processor-change with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rohitp1/libri-alpha-1-Temp-1-processor-change with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rohitp1/libri-alpha-1-Temp-1-processor-change")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("rohitp1/libri-alpha-1-Temp-1-processor-change") model = AutoModelForCTC.from_pretrained("rohitp1/libri-alpha-1-Temp-1-processor-change") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97295c0cda07d87197575dcaa074388796ba1eb4d42d205a3810296f447c31a9
- Size of remote file:
- 208 MB
- SHA256:
- ad7615fdd99f442f39c700ca502cbf18a2bdda82df7e1cf41718b25cf46feb84
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