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@ -181,7 +181,7 @@ mixin codepen(slug, height, default_tab)
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alt_file - [string] alternative file path used in footer and link button
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height - [integer] height of code preview in px
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mixin github(repo, file, alt_file, height, language)
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mixin github(repo, file, height, alt_file, language)
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- var branch = ALPHA ? "develop" : "master"
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- var height = height || 250
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@ -234,7 +234,7 @@ p
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| when you customise spaCy's tokenization rules. When you call #[code nlp]
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| on a text, the custom pipeline component is applied to the #[code Doc]
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+github("spacy", "examples/pipeline/custom_component_entities.py", false, 500)
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+github("spacy", "examples/pipeline/custom_component_entities.py", 500)
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p
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| Wrapping this functionality in a
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@ -255,7 +255,7 @@ p
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| #[code Token] – for example, the capital, latitude/longitude coordinates
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| and even the country flag.
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+github("spacy", "examples/pipeline/custom_component_countries_api.py", false, 500)
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+github("spacy", "examples/pipeline/custom_component_countries_api.py", 500)
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p
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| In this case, all data can be fetched on initialisation in one request.
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@ -50,4 +50,4 @@ p
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| dataset and will be loaded automatically via Thinc's built-in dataset
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| loader.
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+github("spacy", "examples/pipeline/multi_processing.py")
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+github("spacy", "examples/pipeline/multi_processing.py", 500)
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@ -34,7 +34,7 @@ p
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| #[strong character offsets] and #[strong labels] of each entity contained
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| in the texts.
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+github("spacy", "examples/training/train_ner.py")
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+github("spacy", "examples/training/train_ner.py", 500)
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+h(4) Step by step guide
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@ -88,7 +88,7 @@ p
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| recognizer over unlabelled sentences, and adding their annotations to the
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| training set.
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+github("spacy", "examples/training/train_new_entity_type.py")
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+github("spacy", "examples/training/train_new_entity_type.py", 500)
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+h(4) Step by step guide
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@ -8,7 +8,7 @@ p
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| #[strong training examples] and the respective #[strong heads] and
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| #[strong dependency label] for each token of the example texts.
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+github("spacy", "examples/training/train_parser.py")
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+github("spacy", "examples/training/train_parser.py", 500)
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+h(4) Step by step guide
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@ -61,7 +61,7 @@ p
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| #[strong custom tags], as well as a dictionary mapping those tags to the
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| #[+a("http://universaldependencies.github.io/docs/u/pos/index.html") Universal Dependencies scheme].
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+github("spacy", "examples/training/train_tagger.py")
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+github("spacy", "examples/training/train_tagger.py", 500)
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+h(4) Step by step guide
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@ -141,7 +141,7 @@ p
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| of relations: #[code ROOT], #[code PLACE], #[code QUALITY],
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| #[code ATTRIBUTE], #[code TIME] and #[code LOCATION].
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+github("spacy", "examples/training/train_intent_parser.py")
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+github("spacy", "examples/training/train_intent_parser.py", 500)
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+h(4) Step by step guide
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@ -11,7 +11,7 @@ p
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| loader. Predictions are available via
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| #[+api("doc#attributes") #[code Doc.cats]].
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+github("spacy", "examples/training/train_textcat.py")
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+github("spacy", "examples/training/train_textcat.py", 500)
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+h(4) Step by step guide
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@ -179,4 +179,4 @@ include ../_includes/_mixins
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| parameters, and was implemented using #[+a("https://keras.io") Keras]
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| and spaCy.
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+github("spacy", "examples/keras_parikh_entailment/__main__.py", "examples/keras_parikh_entailment")
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+github("spacy", "examples/keras_parikh_entailment/__main__.py", false, "examples/keras_parikh_entailment")
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