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- ---
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- license: mit
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ tags:
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+ - sklearn
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+ - regression
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+ - automotive
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+ - mpg
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+ ---
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+
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+ # Auto MPG Predictor
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+
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+ This model predicts a vehicle's fuel efficiency (miles per gallon) based on its characteristics.
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+
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+ ## Model Details
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+
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+ - Model type: Linear Regression
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+ - Input features: cylinders, displacement, horsepower, weight, acceleration, model_year, origin_Japan, origin_USA
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+ - Target: mpg (miles per gallon)
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+
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+ ## How to Use
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+
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+ ```python
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+ from huggingface_hub import hf_hub_download
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+ import joblib
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+
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+ # Download model and scaler
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+ model_path = hf_hub_download(repo_id="your-username/auto-mpg-regressor", filename="auto_mpg_regressor.joblib")
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+ scaler_path = hf_hub_download(repo_id="your-username/auto-mpg-regressor", filename="scaler.joblib")
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+
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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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+ # Prepare input data (same order as features in config)
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+ import numpy as np
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+ sample_input = np.array([[6, 225, 100, 3233, 15.4, 76, 0, 1]]) # Example input
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+
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+ # Preprocess
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+ scaled_input = scaler.transform(sample_input)
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+
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+ # Predict
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+ prediction = model.predict(scaled_input)
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+ print(f"Predicted MPG: {prediction[0]}")