What are typical embedding sizes used in models for code understanding and generation?

Feb 13, 2023 ... The size of the embedding matrix (WE) is (50000 * 768) for small models, where there are 50000 tokens and 768 dimensions. The unembedding ... Aug 17, 2023 ... Word2Vec can be used to create dense word embeddings that are vectors that have a fixed size, regardless of the size of the vocabulary. This ... Jul 17, 2019 ... Empirical testing (grid search): Jeremy says that in a couple of lessons. For course 2018 - Take a look at @hiromi post on that: The rule of ... Jul 29, 2017 ... Answer. A Word Embedding is just a mapping from words to vectors. Dimensionality in word embeddings refers to the length of these vectors. May 4, 2019 ... The most common powers of 2 for word embeddings are 128 or 256, depending on which order of magnitude is preferred. Share. Share a link to this ... titan-embed-text-v2:0 ) can intake up to 8,192 tokens or 50,000 characters and outputs a vector of 1,024 dimensions. The model is optimized for text retrieval ... Apr 8, 2023 ... The output dimension is mantained, since values coming from each attention head are concatenated and then projected with a matrix WO∈Rhdv×dmodel ... Feb 28, 2025 ... In general, the dimensionality of word embedding refers to the number of dimensions in which the vector representation of a word is defined. Apr 11, 2019 ... Image should be JPG or PNG. Both can be saved down to a lower resolution/smaller size/lower color depth by third party software. My response was solely for the cloud version. Here's a small clarification : I mistook your mention of maximum size for Office Powerpoint Macro , as the file ...