From b15bdb5279583ea648cad4aafa976747237b40da Mon Sep 17 00:00:00 2001 From: ines Date: Sun, 16 Apr 2017 20:35:56 +0200 Subject: [PATCH] Update training docs --- website/docs/usage/training.jade | 27 +++++++++++++++++++-------- 1 file changed, 19 insertions(+), 8 deletions(-) diff --git a/website/docs/usage/training.jade b/website/docs/usage/training.jade index 39f524829..8a5c111bd 100644 --- a/website/docs/usage/training.jade +++ b/website/docs/usage/training.jade @@ -1,13 +1,10 @@ include ../../_includes/_mixins p - | This tutorial describes how to train new statistical models for spaCy's + | This workflow describes how to train new statistical models for spaCy's | part-of-speech tagger, named entity recognizer and dependency parser. - -p - | I'll start with some quick code examples, that describe how to train - | each model. I'll then provide a bit of background about the algorithms, - | and explain how the data and feature templates work. + | Once the model is trained, you can then + | #[+a("/docs/usage/saving-loading") save and load] it. +h(2, "train-pos-tagger") Training the part-of-speech tagger @@ -48,7 +45,21 @@ p p +button(gh("spaCy", "examples/training/train_ner.py"), false, "secondary") Full example -+h(2, "train-entity") Training the dependency parser ++h(2, "extend-entity") Extending the named entity recognizer + +p + | All #[+a("/docs/usage/models") spaCy models] support online learning, so + | you can update a pre-trained model with new examples. You can even add + | new classes to an existing model, to recognise a new entity type, + | part-of-speech, or syntactic relation. Updating an existing model is + | particularly useful as a "quick and dirty solution", if you have only a + | few corrections or annotations. + +p.o-inline-list + +button(gh("spaCy", "examples/training/train_new_entity_type.py"), true, "secondary") Full example + +button("/docs/usage/training-ner", false, "secondary") Usage Workflow + ++h(2, "train-dependency") Training the dependency parser +code. from spacy.vocab import Vocab @@ -67,7 +78,7 @@ p p +button(gh("spaCy", "examples/training/train_parser.py"), false, "secondary") Full example -+h(2, 'feature-templates') Customizing the feature extraction ++h(2, "feature-templates") Customizing the feature extraction p | spaCy currently uses linear models for the tagger, parser and entity