Hi. Suppose I have Thai tokenizer and also I have my own PyTorch trained classifiers. Let says I have 2 classifiers for different purposes. Let them read same sentence and return the prediction as output1 and output2 as follows
output1 = model1(["first_tokenized_word", "second_tokenized_word", ..., "n_th_tokenized_word"] output2 = model2(["first_tokenized_word", "second_tokenized_word", ..., "n_th_tokenized_word"]
- How can I plug my models in to the Rasa pipeline? I have no intention to train the model in the Rasa. Because the training might imbalanced and I can’t use ImbalancedDatasetSampler to fix it.
I have read thee document, but could not be able to understand.
- I have seen the pipeline with adjustable parameter but in the
Component's constructor has no
**kwargs. Then how to supply the my model configuration in
model = RNN(input_size=10, hidden_size=256, n_layper=2, dropout=0.2)