Instructions to use RickyIG/audio_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RickyIG/audio_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="RickyIG/audio_classification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("RickyIG/audio_classification") model = AutoModelForAudioClassification.from_pretrained("RickyIG/audio_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6dbf9a362f01a260733976b36f49e887d5b3cbde490f65b0895d61faf17d447c
- Size of remote file:
- 378 MB
- SHA256:
- bbc5d98985b6dff43b6dba82bfa69634c514205ce203b5f60ed3a15f82cafe28
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