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:
- 99ab88e6f6cd5e75068cc4bc51f81bb03e9b33d24e8ec04d7dcb705769c25c19
- Size of remote file:
- 3.57 kB
- SHA256:
- 2477de57c40737a2d6d06b53e47328451a8423e4e68367e9e56edbd650beae4e
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