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According to the article and the code, my understanding is that the method proposed in this paper is essentially to train a invertible mapping by using the glow model, and then use the original function to transform Bert Embedding to the Gaussian distribution space, and the parameters of the Bert model will not be changed in this process; of course, the label information is not used in the model training process. Finally, when the model is saved, only some relevant parameters of the glow model need to be saved.
Is my understanding correct?
The text was updated successfully, but these errors were encountered:
According to the article and the code, my understanding is that the method proposed in this paper is essentially to train a invertible mapping by using the glow model, and then use the original function to transform Bert Embedding to the Gaussian distribution space, and the parameters of the Bert model will not be changed in this process; of course, the label information is not used in the model training process. Finally, when the model is saved, only some relevant parameters of the glow model need to be saved.
Is my understanding correct?
The text was updated successfully, but these errors were encountered: