Instructions to use yaongua/korean_kws2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yaongua/korean_kws2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="yaongua/korean_kws2")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("yaongua/korean_kws2") model = AutoModelForAudioClassification.from_pretrained("yaongua/korean_kws2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb9627a8b27a67da4d948328c0e4dd4d01852d44dab06fdfd5df0ddf83bf9a96
- Size of remote file:
- 5.2 kB
- SHA256:
- 2e1e98ef6c41376cd0d3566fb89902a4e66c9e99ab9840cf443e3e8e4544b6bf
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