Instructions to use imha123/audio_cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imha123/audio_cls with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="imha123/audio_cls")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("imha123/audio_cls") model = AutoModelForAudioClassification.from_pretrained("imha123/audio_cls") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13b02479c88acfc042e571147b29e3704ef29e03e634f7f9e8107a91ca9051e1
- Size of remote file:
- 5.78 kB
- SHA256:
- 315046e3c936883e4e423906c641cebcd74b1631fca432c5a1cb0dce218871a1
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