fname = 'C:\\Users\\tauseef\\Desktop\\keras\\tutorials\\BestWeights.hdf5'
modelConfig = joblib.load('modelConfig.pkl')
recreatedModel = Sequential.from_config(modelConfig)
recreatedModel.load_weights(fname)
unseenTestData = np.genfromtxt(
    'C:\\Users\\tauseef\\Desktop\\keras\\arrayOf100Rows257Columns.txt',
    delimiter=' ')
X_test = unseenTestData
standard_scalerX = StandardScaler()
standard_scalerX.fit(X_test)
X_test_std = standard_scalerX.transform(X_test)
X_test_std = X_test_std.astype('float32')
unseenData_predictions = recreatedModel.predict(X_test_std)
Keras, how do I predict after I trained a model?