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