Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use devkya/ko-commands-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devkya/ko-commands-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="devkya/ko-commands-classification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("devkya/ko-commands-classification") model = AutoModelForAudioClassification.from_pretrained("devkya/ko-commands-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3a73d2754e9ad7ea5e355aa6ea11e91ac20b86208a64d15e3c280f35ddaf7a2
- Size of remote file:
- 378 MB
- SHA256:
- ce2fdfe68f26933c64eab3ba813a8c9d865c47b32351ca65cef7a67442b69eb8
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