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Upload model files and documentation

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  1. README.md +37 -0
  2. models/model.joblib +3 -0
  3. models/scaler.joblib +3 -0
README.md ADDED
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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+ ## License
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+
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+ MIT License
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