embedding dimension so by embedding one heart word it's basically if we went looking up what what what the corresponding word embedding is and the C bar model would just average the embeddings of your surrounding words and try to identify the embedding of your missing word and the skip grammar model would basically try to use the word embedding and do an individual softmax over all the surrounding words so let's actually look into the math of how this works out so consider the Cibo Matto and here you're trying to maximize the log