corpus = NLPTaskDataFetcher.load_classification_corpus(Path('../'), test_file='test.csv', dev_file='dev.csv', train_file='train.csv')
            word_embeddings = [WordEmbeddings('glove'), FlairEmbeddings('news-forward-fast'), FlairEmbeddings('news-backward-fast')]
            document_embeddings = DocumentLSTMEmbeddings(word_embeddings, hidden_size=512, reproject_words=True, reproject_words_dimension=256)
            classifier = TextClassifier(document_embeddings, label_dictionary=corpus.make_label_dictionary(), multi_label=False)
            trainer = ModelTrainer(classifier, corpus)
            
            trainer.train('../', max_epochs=10) # error cpuinfo