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Just need to access the underlying model via the models_ attribute of MLForecast and plot using LightGBM's function:

import lightgbm as lgb

lgb.plot_importance(mlf.models_['LGBMRegressor'], max_num_features=5)

Here mlf is the mlforecast class after fitting and max_num_features is the number of the top features to plot.

Cc @José Morales