Instructions to use bryandts/audio_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bryandts/audio_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="bryandts/audio_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("bryandts/audio_classification") model = AutoModelForAudioClassification.from_pretrained("bryandts/audio_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from bryandts/audio_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/bryandts/audio_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://bryandts/audio_classification/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/bryandts/audio_classification/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 5181f5b8914a403c0e3de9b215193323373276249a70693d0bbeeadfdb827d38
- Size of remote file:
- 4.03 kB
- SHA256:
- ad8e1aa791a9c803eb5ca6d9520cdf3f4afbdb761f57b8d7e025d529ab9a8f3b
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