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Ines Montani 2019-04-13 17:58:26 +02:00
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@ -274,7 +274,7 @@ an approximate language-modeling objective. Specifically, we load pre-trained
vectors, and train a component like a CNN, BiLSTM, etc to predict vectors which vectors, and train a component like a CNN, BiLSTM, etc to predict vectors which
match the pre-trained ones. The weights are saved to a directory after each match the pre-trained ones. The weights are saved to a directory after each
epoch. You can then pass a path to one of these pre-trained weights files to the epoch. You can then pass a path to one of these pre-trained weights files to the
'spacy train' command. `spacy train` command.
This technique may be especially helpful if you have little labelled data. This technique may be especially helpful if you have little labelled data.
However, it's still quite experimental, so your mileage may vary. To load the However, it's still quite experimental, so your mileage may vary. To load the