Por que esse código em python não funciona?

Estou tentando executar isso

Mensagem de erro:

ValueError                                Traceback (most recent call last)
/tmp/ipykernel_3927/3218782290.py in <module>
      6 
      7 model = LinearRegression()
----> 8 model.fit(array1, array2)

~/anaconda3/lib/python3.9/site-packages/sklearn/linear_model/_base.py in fit(self, X, y, sample_weight)
    660         accept_sparse = False if self.positive else ["csr", "csc", "coo"]
    661 
--> 662         X, y = self._validate_data(
    663             X, y, accept_sparse=accept_sparse, y_numeric=True, multi_output=True
    664         )

~/anaconda3/lib/python3.9/site-packages/sklearn/base.py in _validate_data(self, X, y, reset, validate_separately, **check_params)
    579                 y = check_array(y, **check_y_params)
    580             else:
--> 581                 X, y = check_X_y(X, y, **check_params)
    582             out = X, y
    583 

~/anaconda3/lib/python3.9/site-packages/sklearn/utils/validation.py in check_X_y(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, estimator)
    962         raise ValueError("y cannot be None")
    963 
--> 964     X = check_array(
    965         X,
    966         accept_sparse=accept_sparse,

~/anaconda3/lib/python3.9/site-packages/sklearn/utils/validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator)
    767             # If input is 1D raise error
    768             if array.ndim == 1:
--> 769                 raise ValueError(
    770                     "Expected 2D array, got 1D array instead:\narray={}.\n"
    771                     "Reshape your data either using array.reshape(-1, 1) if "

ValueError: Expected 2D array, got 1D array instead:
array=[0 1 2 3 4 5].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.