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README.md

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 ---
-title: Ml Models Energy
-emoji: 💻
-colorFrom: indigo
-colorTo: pink
+title: Energy ML Prediction System
+emoji: ⚡
+colorFrom: blue
+colorTo: green
 sdk: gradio
-sdk_version: 5.42.0
+sdk_version: 4.0.0
 app_file: app.py
 pinned: false
+license: mit
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Energy ML Prediction System
+
+AI-powered energy consumption prediction and threshold exceedance detection.
+
+## Models
+
+- **Threshold Detection**: Random Forest classifier (AUC = 0.94)
+- **Energy Prediction**: Random Forest & XGBoost regressors
+- **Performance**: R² up to 0.72, MAE as low as 0.53 MWh
+
+## Features
+
+- Real-time predictions via simple JSON interface
+- Multiple model comparison (RF vs XGBoost)
+- Threshold exceedance probability (8.3 and 9.0 MWh)
+- Secure access with authentication
+
+## Usage
+
+1. Select your model
+2. Input JSON configuration
+3. Get instant predictions
+
+## Authentication
+
+Login required for access.
+- Username: admin
+- Password: energy123
+
+---
+*Built with Gradio • Powered by scikit-learn & XGBoost*

requirements.txt

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+gradio>=4.0.0
+pandas>=1.5.0
+numpy>=1.24.0
+scikit-learn>=1.3.0
+xgboost>=1.7.0
+pickle5

rf_energy_model.pkl

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threshold_model_83.pkl

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threshold_model_90.pkl

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xgboost_energy_model.pkl

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