Instructions to use abdelhalim/Shower_Sound_Recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdelhalim/Shower_Sound_Recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="abdelhalim/Shower_Sound_Recognition")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("abdelhalim/Shower_Sound_Recognition") model = AutoModelForAudioClassification.from_pretrained("abdelhalim/Shower_Sound_Recognition") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 233717e7456c66b457a246edeaa65bbcabf3e7621e3e702916790475211697cf
- Size of remote file:
- 2.86 kB
- SHA256:
- 083e996cadfcf8a6ac62b5ad3d49c66114499251108020fcbe91230726fdb247
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