do I need to pass user and item matrixes to predict method for known users and items in fit step

[unrepeat]

I've fitted the model with user and items matrixes: model.fit( int_m, user_features = user_matrix, item_features = item_matrix) Let's say I want to have predictions for one user and few items, can I do like this: model.predict(1,[2,5,7,8,9]) or I need to again pass matrixes like this: model.predict(1,[2,5,7,8],user_features = user_matrix, item_features = item_matrix)) Im asking because results are different: [ -2.8424215 -12.3355665 -9.75003 -8.55455 -3.7264912] vs [-119.41913 -117.80002 -116.015114 -117.74599 -119.52765 ]