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:
- a8c341b4b302af36819f60b530cb6a2b06f55b9ab06858efdcfe9135e44713c9
- Size of remote file:
- 4.6 kB
- SHA256:
- f358f4df4595616b7ff2492095160dd55227d43b5e4946d16bec1e802e11ddcc
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