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:
- 43b24d2e9da9d6d2f7bbbea180175ea465057d3b7c39e25959ea834a84e6d280
- Size of remote file:
- 151 MB
- SHA256:
- bd94ed6cc8eb82c95e5af9e6b6700e8f504ac15a174c54d19a2f83f452b2b495
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