Instructions to use DerrickLegacy256/bee-audio-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use DerrickLegacy256/bee-audio-classifier with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("DerrickLegacy256/bee-audio-classifier", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Auto-deploy 2026-05-19 11:52 UTC
Browse files- README.md +1 -1
- gradient_boosting_model.pkl +2 -2
- label_encoder.pkl +2 -2
- random_forest_model.pkl +2 -2
- svm_rbf_model.pkl +2 -2
- xgboost_model.pkl +2 -2
README.md
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5-class audio classifier for bee colony health monitoring.
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Trained on segmented hive recordings using MFCC-based feature extraction.
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> Last updated: 2026-05-
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## Classes
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5-class audio classifier for bee colony health monitoring.
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Trained on segmented hive recordings using MFCC-based feature extraction.
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> Last updated: 2026-05-19 11:52 UTC
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## Classes
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gradient_boosting_model.pkl
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label_encoder.pkl
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random_forest_model.pkl
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svm_rbf_model.pkl
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xgboost_model.pkl
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