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@ -445,7 +445,8 @@ an approximate language-modeling objective. Specifically, we load pretrained
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vectors, and train a component like a CNN, BiLSTM, etc to predict vectors which
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match the pretrained 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 pretrained weights files to the
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`spacy train` command.
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`spacy train` command. You can try to use a few with low `Loss` values reported
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in the output.
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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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