def METHOD_NAME(input_path: str):
    with open(os.path.join(input_path, 'wordembedding_config.json'), 'r') as fIn:
        config = json.METHOD_NAME(fIn)
    tokenizer_class = import_from_string(config['tokenizer_class'])
    tokenizer = tokenizer_class.METHOD_NAME(input_path)
    weights = torch.METHOD_NAME(os.path.join(input_path, 'pytorch_model.bin'), map_location=torch.device('cpu'))
    embedding_weights = weights['emb_layer.weight']
    model = WordEmbeddings(tokenizer=tokenizer, embedding_weights=embedding_weights, update_embeddings=config['update_embeddings'])
    return model