Instructions to use kurianbenoy/whisper-small-ml-gmasc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kurianbenoy/whisper-small-ml-gmasc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kurianbenoy/whisper-small-ml-gmasc")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("kurianbenoy/whisper-small-ml-gmasc") model = AutoModelForSpeechSeq2Seq.from_pretrained("kurianbenoy/whisper-small-ml-gmasc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ab41c722027a8beae54a9d0046b51ff79a2f56c44f6f440f533a54e63100e15
- Size of remote file:
- 967 MB
- SHA256:
- 88f4bbdd125339443a4cbd333aed5ba8699aa4e1d3ec66f0663f62e681da7696
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