Word2Vec Model Training and Loading with Gensim

This function uses the Word2Vec model from the gensim library to train a word vector model and saves the model to a file. Then, it loads the model from the file.

Technology Stack : gensim

Code Type : The type of code

Code Difficulty : Intermediate

                
                    
def word2vec_model_training(text_list):
    from gensim.models import Word2Vec
    from gensim.models import KeyedVectors
    
    # Create a Word2Vec model
    model = Word2Vec(text_list, vector_size=100, window=5, min_count=1, workers=4)
    
    # Save the model to a file
    model.save("word2vec_model")
    
    # Load the model from a file
    loaded_model = KeyedVectors.load("word2vec_model")
    
    return loaded_model