Instructions to use bgstud/whisper-ft-commonvoice-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bgstud/whisper-ft-commonvoice-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bgstud/whisper-ft-commonvoice-en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bgstud/whisper-ft-commonvoice-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("bgstud/whisper-ft-commonvoice-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a75955542e2504d904532c3abe4d91e10759b8c7f2dcee8c791918abe0f1c394
- Size of remote file:
- 151 MB
- SHA256:
- 1ce0651e6c8e248b92ed9b3d86a675c43ec932720355f529ae5ffef8e7b32713
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