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
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:c0b44af3ecd2aa7168c780b21566e7788ea9bb9e376556bec2216142dc7d2d59
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size 151061672
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