It exponentiates scores after a numerical-stability adjustment and divides each value by their total. Models use the result as a categorical probability distribution for classification or token selection.
Softmax converts a vector of real-valued scores into nonnegative values that sum to one.
It exponentiates scores after a numerical-stability adjustment and divides each value by their total. Models use the result as a categorical probability distribution for classification or token selection.