# Exporting Models

Predictive models can be saved and re-used. Models are saved in Python pickle format.

## Save model

Models first require data for training. They output a trained model, which can be saved with Save Model widget in the pickle format.

## Load model

Models can be reused in different Orange workflows. Load Model loads a trained model, which can be used in Predictions and elsewhere.

## Load in Python

Models can also be imported directly into Python and used in a script.

    import pickle

    with open('model.pkcls', 'rb') as model:
        lr = pickle.loads(model)

    lr
    >> LogisticRegressionClassifier(skl_model=LogisticRegression(C=1,
                                    class_weight=None, dual=False,
                                    fit_intercept=True, intercept_scaling=1.0,
                                    l1_ratio=None, max_iter=10000,
                                    multi_class='auto', n_jobs=1, penalty='l2',
                                    random_state=0, solver='lbfgs', tol=0.0001,
                                    verbose=0, warm_start=False))