I am trying to fit a Logistic regression model from Scikit-Learn package. Below is my code

from sklearn.datasets import load_digits
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split

digits = load_digits()
x_train, x_test, y_train, y_test = train_test_split(digits.data, digits.target, test_size=0.25, random_state=0)

model = LogisticRegression()
fit = model.fit(x_train, y_train)

However I am not able to find any routine to estimate the Standard Error of the estimated coefficients.

Is there any method available to estimate the SE from Scikit-Learn?