Instructions to use bgstud/whisper-tiny-libirAugm-vs-commonAccentAug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bgstud/whisper-tiny-libirAugm-vs-commonAccentAug with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bgstud/whisper-tiny-libirAugm-vs-commonAccentAug")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bgstud/whisper-tiny-libirAugm-vs-commonAccentAug") model = AutoModelForSpeechSeq2Seq.from_pretrained("bgstud/whisper-tiny-libirAugm-vs-commonAccentAug") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c99404b30b6bd7b3373608936f9670db19856c906f15a33e72268806df5fd8b
- Size of remote file:
- 151 MB
- SHA256:
- 80f1f6ef50b26926e14552c3db9612421e40edb7ce54a92896b9f0f2cef66774
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