Word2Vec Model Creation and Loading Example

This function uses the Word2Vec model from the gensim library to convert input text into word vectors and saves and loads the model.

Technology Stack : gensim, Word2Vec, LineSentence

Code Type : Function

Code Difficulty : Intermediate

                
                    
def word2vec_model_example(input_text):
    from gensim.models import Word2Vec
    from gensim.models.word2vec import LineSentence

    # Create a Word2Vec model
    model = Word2Vec(LineSentence(input_text), vector_size=100, window=5, min_count=5, workers=4)

    # Save the model to disk
    model.save("word2vec_model")

    # Load the model from disk
    loaded_model = Word2Vec.load("word2vec_model")

    # Get the vector for a specific word
    word_vector = loaded_model.wv["word"]

    return word_vector