Instructions to use bgstud/whisper-tiny-commonAccentAug-vs-libirAugm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bgstud/whisper-tiny-commonAccentAug-vs-libirAugm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bgstud/whisper-tiny-commonAccentAug-vs-libirAugm")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bgstud/whisper-tiny-commonAccentAug-vs-libirAugm") model = AutoModelForSpeechSeq2Seq.from_pretrained("bgstud/whisper-tiny-commonAccentAug-vs-libirAugm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d56d54698407dffec146b94b409b59e29337c00e21ccdafcb66daf0a44330487
- Size of remote file:
- 3.57 kB
- SHA256:
- 7e14ba5604a48910414a99734d3bd9205ea46fabb6bc6606d0e88a6fae8f1190
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