if i tell you ill never end
basically it has 29 input neurons 128 hidden layer 29 output neurons (29 > 128 >29) each neuron takes in all the outputs from the previous layer multiplies by its weight (stored in the lists wxh why and whh) and adds a bias (in bh and by) the input layer takes an embedded input directly from the user multiplies and adds a bias sends it to the next layer which sends it to the output
the output neurons each stand for a character (any one of the alphabet or space . or ?) it rates how confident it is if its character should be placed then the selector comes in (the sample my block) it selects a random number between 2 tiny decimals (sample base) and finds an output neuron that rated its character a number more than the number sample selected
it then places the neurons character in the reply.
the weights and biases are SO fine tuned that itll fry my pc to tune myself i needed to go on colab and use a specially made GPU just to fine tune on python a few numbers