Instructions to use Priyanship/base_sami_22k_ftpseudo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Priyanship/base_sami_22k_ftpseudo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Priyanship/base_sami_22k_ftpseudo")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Priyanship/base_sami_22k_ftpseudo") model = AutoModelForCTC.from_pretrained("Priyanship/base_sami_22k_ftpseudo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- afa1bfd43022291c7c0de248e2406ea49d6eb73321bc1db521bbd68c1837825a
- Size of remote file:
- 5.56 kB
- SHA256:
- a8bb491e505795e0b0146ab9733748a2e8c80374fb885e742eeba1fc3b0fcb23
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