Instructions to use bh4/whisper-ben with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bh4/whisper-ben with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bh4/whisper-ben")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bh4/whisper-ben") model = AutoModelForSpeechSeq2Seq.from_pretrained("bh4/whisper-ben") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6397631324b406ff5b7224a12f17ca0c4fe81f55e5fc57b2befc423c06ddd83b
- Size of remote file:
- 1.53 GB
- SHA256:
- 87ab8edfa81f02591422cc41607d1d437e1cb55578ca19629a238a11a4b23214
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