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Upload model files and documentation
Browse files- README.md +37 -0
- models/model.joblib +3 -0
- models/scaler.joblib +3 -0
README.md
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# Healing Music Classifier
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This is a machine learning model that predicts the healing potential of music tracks. The model analyzes various audio features to determine how likely a piece of music is to have healing properties.
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## Model Details
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- **Type**: Random Forest Classifier
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- **Features**: MFCC, Spectral Features, Chroma Features
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- **Input**: Audio file (MP3 or WAV format)
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- **Output**: Healing probability score (0-1)
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## Usage
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```python
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import joblib
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from huggingface_hub import hf_hub_download
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# Download model files
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model_path = hf_hub_download(repo_id="healing-music-classifier", filename="models/model.joblib")
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scaler_path = hf_hub_download(repo_id="healing-music-classifier", filename="models/scaler.joblib")
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# Load model and scaler
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model = joblib.load(model_path)
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scaler = joblib.load(scaler_path)
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# Use the model (after feature extraction)
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# prediction = model.predict_proba(scaled_features)[0][1]
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```
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## Web Interface
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You can try the model directly through our Streamlit interface at:
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https://huggingface.co/spaces/[your-username]/healing-music-classifier
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## License
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MIT License
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models/model.joblib
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version https://git-lfs.github.com/spec/v1
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oid sha256:08e5c37f829bca6256348ab94b6450748ceba8dc4014b37ce01e98e8038b618d
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size 166857
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models/scaler.joblib
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version https://git-lfs.github.com/spec/v1
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oid sha256:14e0cd7fc9d652cf93b29141e4ef46f8436edfd576c2d260262d105e21a36e77
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size 1496
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