Instructions to use Rifky/whisper-small-ko-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rifky/whisper-small-ko-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Rifky/whisper-small-ko-test")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Rifky/whisper-small-ko-test") model = AutoModelForSpeechSeq2Seq.from_pretrained("Rifky/whisper-small-ko-test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2067c548c549b8aca4d3fd564f88e9e1787874ad0bc51462904d0acd08b56dff
- Size of remote file:
- 4.09 kB
- SHA256:
- 3dda9099005037c6ae47215a91360125513f28f0ade7003a2412d83d50db0723
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