test.toml

# The full config for test the BERT-QTC model.
# The task of this config. Available values: 'train' | 'test'.
task = 'test'
# The text to be tested.
text = 'The text to be predicted.'
# The path of the trained model, which will be loaded.
model_path = 'decoder.pdparams'
# The number of the filters
num_filter = 1
# The size of the kernel
kernel_size = 5
# The depth of the quantum circuit
circuit_depth = 2
# The length to pad
padding = 2
# The pretrained bert model
bert_model = 'bert-base-chinese'
# The size of the hidden state obtained through the BERT model
hidden_size = 768
# The classes of input text to be predicted.
classes = ['火车', '音乐', '天气', '短信', '电话', '航班', '新闻']