Instructions to use SungBeom/whisper-small-ko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SungBeom/whisper-small-ko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SungBeom/whisper-small-ko")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("SungBeom/whisper-small-ko") model = AutoModelForSpeechSeq2Seq.from_pretrained("SungBeom/whisper-small-ko") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63f37043d72d418079f894bcf04996c0af1dac62f4df90853c2e38a5bbd19a5a
- Size of remote file:
- 967 MB
- SHA256:
- 88715d85b0081219a9de261f2c25ecb2ffed79ac2fe46fcc8c4d8fd809349e33
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