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Update training tutorial
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@ -27,12 +27,13 @@ p #[+a("https://github.com/" + SOCIAL.github + "/spaCy/examples/training/train_t
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from spacy.vocab import Vocab
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from spacy.vocab import Vocab
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from spacy.pipeline import EntityRecognizer
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from spacy.pipeline import EntityRecognizer
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from spacy.tokens import Doc
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from spacy.tokens import Doc
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from spacy.gold import GoldParse
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vocab = Vocab()
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vocab = Vocab()
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entity = EntityRecognizer(vocab, entity_types=['PERSON', 'LOC'])
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entity = EntityRecognizer(vocab, entity_types=['PERSON', 'LOC'])
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doc = Doc(vocab, words=['Who', 'is', 'Shaka', 'Khan', '?'])
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doc = Doc(vocab, words=['Who', 'is', 'Shaka', 'Khan', '?'])
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entity.update(doc, ['O', 'O', 'B-PERSON', 'L-PERSON', 'O'])
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entity.update(doc, GoldParse(doc, entities=['O', 'O', 'B-PERSON', 'L-PERSON', 'O']))
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entity.model.end_training()
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entity.model.end_training()
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@ -49,8 +50,7 @@ p #[+a("https://github.com/" + SOCIAL.github + "/spaCy/examples/training/train_n
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parser = DependencyParser(vocab, labels=['nsubj', 'compound', 'dobj', 'punct'])
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parser = DependencyParser(vocab, labels=['nsubj', 'compound', 'dobj', 'punct'])
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doc = Doc(vocab, words=['Who', 'is', 'Shaka', 'Khan', '?'])
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doc = Doc(vocab, words=['Who', 'is', 'Shaka', 'Khan', '?'])
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parser.update(doc, [(1, 'nsubj'), (1, 'ROOT'), (3, 'compound'), (1, 'dobj'),
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parser.update(doc, GoldParse(doc, heads=[1, 1, 3, 1, 1,], deps=['nsubj', 'ROOT', 'compound', 'dobj', 'punct']))
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(1, 'punct')])
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parser.model.end_training()
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parser.model.end_training()
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