Instructions to use glenn2/whisper-small-b4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use glenn2/whisper-small-b4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="glenn2/whisper-small-b4")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("glenn2/whisper-small-b4") model = AutoModelForSpeechSeq2Seq.from_pretrained("glenn2/whisper-small-b4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f2911e18b7bfcafcb1622a2de6457475cc8a30bcbb46d77de99a53840944c92
- Size of remote file:
- 5.05 kB
- SHA256:
- c37ff6706ac62c5a90347822aa4b0c7382af89e87a99e238da6ba13d5f8d2011
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