中文预训练模型ERNIE该如何使用

ERNIE is a Chinese pre-training model proposed by Baidu. It is based on the English BERT model and has been pre-trained on a large amount of Chinese data. ERNIE can be used for tasks such as text classification, information extraction, and question answering.

To use ERNIE, you first need to download the model from the Baidu Cloud. Then, you can use the model to train your own models for specific tasks. For example, to train a text classifier, you can use the following command:

python run_classifier.py \

--task_name=CLASSIFICATION \

--do_train=true \

--do_eval=true \

--data_dir=DATA_DIR \

--vocab_file=ERNIE_VOCAB_FILE \

--bert_config_file=ERNIE_CONFIG_FILE \

--init_checkpoint=ERNIE_INIT_CHECKPOINT \

--max_seq_length=128 \

--train_batch_size=32 \

--learning_rate=2e-5 \

--num_train_epochs=3.0 \

--output_dir=OUTPUT_DIR

Where DATA_DIR is the directory containing the training data, and OUTPUT_DIR is the directory where the trained model will be saved.

ERNIE can also be used for other tasks such as information extraction and question answering. For more information, please refer to the ERNIE documentation.