Instructions to use heado/korean_kws with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use heado/korean_kws with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="heado/korean_kws")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("heado/korean_kws") model = AutoModelForAudioClassification.from_pretrained("heado/korean_kws") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 791f59d1ce816c9ee36d280c1bf7db022f76915eb284afcdd5f9773c9717caf5
- Size of remote file:
- 5.84 kB
- SHA256:
- 8b0fe63ffae1ccba4420ea230b0981bed41956d625067cafecd401691635eb88
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.