Instructions to use kresnik/whisper-medium-ko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kresnik/whisper-medium-ko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kresnik/whisper-medium-ko")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("kresnik/whisper-medium-ko") model = AutoModelForSpeechSeq2Seq.from_pretrained("kresnik/whisper-medium-ko") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1af35039ea106f1c1ac0e23eb338a27645a9b2f53945b06f0b2c61ea237309eb
- Size of remote file:
- 3.06 GB
- SHA256:
- 36e8b382b33e9c362e963000922dc7290c0a7d56291995f9371bda6f79f7391b
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