R: Read a binary word2vec model from disk

read.word2vec {word2vec} | R Documentation

## Read a binary word2vec model from disk

### Description

Read a binary word2vec model from disk

### Usage

    read.word2vec(file, normalize = FALSE)

### Arguments

`file` | the path to the model file
`normalize` | logical indicating to normalize the embeddings by dividing by the factor (sqrt(sum(x . x) / length(x))). Defaults to FALSE.

### Value

an object of class w2v which is a list with elements

- model: a Rcpp pointer to the model

- model_path: the path to the model on disk

- dim: the dimension of the embedding matrix

- n: the number of words in the vocabulary

### Examples

    path  <- system.file(package = "word2vec", "models", "example.bin")
    model <- read.word2vec(path)
    vocab <- summary(model, type = "vocabulary")
    emb <- predict(model, c("bus", "naar", "unknownword"), type = "embedding")
    emb
    nn  <- predict(model, c("bus", "toilet"), type = "nearest")
    nn

    # Do some calculations with the vectors and find similar terms to these
    emb <- as.matrix(model)
    vector <- emb["gastvrouw", ] - emb["gastvrij", ]
    predict(model, vector, type = "nearest", top_n = 5)
    vectors <- emb[c("gastheer", "gastvrouw"), ]
    vectors <- rbind(vectors, avg = colMeans(vectors))
    predict(model, vectors, type = "nearest", top_n = 10)

[Package word2vec version 0.3.4 Index]