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:
- 4e5ded02e5b360b41a3c900b5754347d99a3addc4cb59242648aedd55f4b7a2e
- Size of remote file:
- 3.58 kB
- SHA256:
- 027cdd889627ba9bd60f9a6d706d5f1d5de2b9fef0cd2b6a6eaccb820b4a188b
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