I am working on a text classification problem, that is, given some text, I need to assign to it certain given labels.
I have tried using fast-text library by Facebook, which has two utilities of interest to me:
A) Word Vectors with pre-trained models
B) Text Classification utilities
However, it seems that these are completely independent tools as I have been unable to find any tutorials that merge these two utilities.
What I want is to be able to classify some text, by taking advantage of the pre-trained models of the Word-Vectors. Is there any way to do this?
FastText supervised training has -pretrainedVectors
argument which can be used like this:
$ ./fasttext supervised -input train.txt -output model -epoch 25 \
-wordNgrams 2 -dim 300 -loss hs -thread 7 -minCount 1 \
-lr 1.0 -verbose 2 -pretrainedVectors wiki.ru.vec
Few things to consider:
-dim 300
argument.-loss hs
)