spaCy/examples
2017-07-29 21:59:27 +02:00
..
inventory_count Rename inventory count example 2016-11-01 02:30:22 +01:00
keras_parikh_entailment Corretions for model test example 2017-05-03 22:41:23 +08:00
training Clarify train textcat example 2017-07-29 21:59:27 +02:00
_handler.py * Add _handler to resolve Issue #123 2015-10-15 02:44:23 +11:00
chainer_sentiment.py Set vectors in chainer example 2016-11-19 18:42:58 -06:00
deep_learning_keras.py Fix use of dropout in sentiment analysis LSTM example 2016-12-20 16:26:38 -06:00
get_parse_subregions.py move displacy to its own subdomain 2016-02-19 14:03:52 +01:00
information_extraction.py * Tweak information extraction example 2015-10-06 10:35:49 +11:00
matcher_example.py * Add clarifying comment 2015-09-27 18:17:41 +10:00
multi_word_matches.py * Filter out phrases that consist of common, lower-case words. 2015-10-09 12:47:43 +11:00
nn_text_class.py Add setup directions for data dir 2016-11-13 10:08:16 -08:00
parallel_parse.py added batch_size as keyword argument 2016-03-10 14:16:34 -08:00
pos_tag.py Fix formatting and typo (closes #967) 2017-04-16 23:56:12 +02:00
README.md Add README.md to examples 2016-11-01 01:14:04 +01:00
twitter_filter.py * Begin rewriting twitter_filter examples 2015-08-22 22:12:26 +02:00

spaCy examples

The examples are Python scripts with well-behaved command line interfaces. For a full list of spaCy tutorials and code snippets, see the documentation.

How to run an example

For example, to run the nn_text_class.py script, do:

$ python examples/nn_text_class.py
usage: nn_text_class.py [-h] [-d 3] [-H 300] [-i 5] [-w 40000] [-b 24]
                        [-r 0.3] [-p 1e-05] [-e 0.005]
                        data_dir
nn_text_class.py: error: too few arguments

You can print detailed help with the -h argument.

While we try to keep the examples up to date, they are not currently exercised by the test suite, as some of them require significant data downloads or take time to train. If you find that an example is no longer running, please tell us! We know there's nothing worse than trying to figure out what you're doing wrong, and it turns out your code was never the problem.