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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("devkya/ko-commands-classification") model = AutoModelForAudioClassification.from_pretrained("devkya/ko-commands-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from devkya/ko-commands-classification: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/devkya/ko-commands-classification/resolve/main/training_args.bin
- Command line
-
hf download hf://devkya/ko-commands-classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/devkya/ko-commands-classification/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 99902b7292e6f03c690dc6f708ee6324922fcc9b6caefbed2010a871e1e3e176
- Size of remote file:
- 5.05 kB
- SHA256:
- 1c4cd43a5b49d79b9d31f87a2df934521090dc85372e5b516bb6bb26a1ba85e8
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