Instructions to use yaboidimsum/audio_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yaboidimsum/audio_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="yaboidimsum/audio_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("yaboidimsum/audio_classification") model = AutoModelForAudioClassification.from_pretrained("yaboidimsum/audio_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from yaboidimsum/audio_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/yaboidimsum/audio_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://yaboidimsum/audio_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/yaboidimsum/audio_classification/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- e84f92ec9b992dcb9a52be697a0bb3d700e223c76c053ded2ae6eb1d36a4e035
- Size of remote file:
- 4.09 kB
- SHA256:
- d8b2d33d76c57bbb686d6038bc35b99dbd797a5632a045b57e69bc8e5c564963
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