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Healing Music Classifier
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.
Model Details
- Type: Random Forest Classifier
- Features: MFCC, Spectral Features, Chroma Features
- Input: Audio file (MP3 or WAV format)
- Output: Healing probability score (0-1)
Usage
import joblib
from huggingface_hub import hf_hub_download
# Download model files
model_path = hf_hub_download(repo_id="healing-music-classifier", filename="models/model.joblib")
scaler_path = hf_hub_download(repo_id="healing-music-classifier", filename="models/scaler.joblib")
# Load model and scaler
model = joblib.load(model_path)
scaler = joblib.load(scaler_path)
# Use the model (after feature extraction)
# prediction = model.predict_proba(scaled_features)[0][1]
Web Interface
You can try the model directly through our Streamlit interface at: https://huggingface.co./spaces/[your-username]/healing-music-classifier
License
MIT License