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:
- b67c48cc0c14b09237c33427f12381cc8b5b49c0b6424de6bcad26992e58c8d9
- Size of remote file:
- 3.57 kB
- SHA256:
- c9994db5b2c2fb423e24e229edbd905c5922abd34aee3fe2d7f1f6aac80b02e8
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