Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Korean
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use TheoJo/whisper-tiny-ko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheoJo/whisper-tiny-ko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TheoJo/whisper-tiny-ko")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("TheoJo/whisper-tiny-ko") model = AutoModelForSpeechSeq2Seq.from_pretrained("TheoJo/whisper-tiny-ko") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c62227560c9ef3894308144198e2c7477fe791d7a9d99d03666de17139f586ab
- Size of remote file:
- 151 MB
- SHA256:
- f3843686519777a4550909e8bd4961dcf7425e7183295f03d09a433a271f0887
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.