Reads a pre-trained word2vec word embedding model in the binary format. Note that it shows a progress bar during reading the data.
MATLAB R2019b
Text Analytics Toolbox Required.
emb = readW2Vbin(filename)
Use readW2Vbin
to read a pre-trained word2vec word embedding model in the binary format. It assumes that the file is written in the following format.
- The data before the first
0x20
(space) are ascii characters representing the number of vocabularies of the model , while the data between the first0x20
and the first0x10
(newline) represent the dimension of the word vector. (e.g.,[ 51 48 48 48 48 48 48 32 51 48 48 10]
means 3 milion words embedded into 300 dimensions. ) - The main body, which consists of sequence of word-vector pairs, begins right after the newline character. One word-vector pair consists of a sequence of bytes that represents a word, space (0x20), and a sequence of binary data that represents the embedded vector corresponding to the word in single precision (32bit) format. The length of the vector data is 4bytes times number of dimensions (e.g., 1200 bytes for 300 dimension).
filename
- Name the pre-trained word2vec model file in the binary format, specified as a string scalar or character vector.
emb - Word embedding, returned as a wordEmbedding
object.
This function was tested with the "GoogleNews-vectors-negative300.bin" from the word2vec web (https://code.google.com/archive/p/word2vec/). It took about a minute to read the 3.5GB file.