Instructions to use gabrielyang/audioclassification_ko_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gabrielyang/audioclassification_ko_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="gabrielyang/audioclassification_ko_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("gabrielyang/audioclassification_ko_model") model = AutoModelForAudioClassification.from_pretrained("gabrielyang/audioclassification_ko_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gabrielyang/audioclassification_ko_model: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/gabrielyang/audioclassification_ko_model/resolve/main/training_args.bin
- Command line
-
hf download hf://gabrielyang/audioclassification_ko_model/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/gabrielyang/audioclassification_ko_model/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- fdc0a6aa2f72a4e8b689f157e3ccc17ef4332000fc4d7b57531e3b7dc4635d3d
- Size of remote file:
- 3.64 kB
- SHA256:
- 1c6cc6500b4f6164edb9830f652dee2892a994c8d5ca682b71b85a0e376d97bc
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