* Prevent Tagger model init with 0 labels
Raise an error before trying to initialize a tagger model with 0 labels.
* Add dummy tagger label for test
* Remove tagless tagger model initializiation
* Fix error number after merge
* Add dummy tagger label to test
* Fix formatting
Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
* rename to spacy-transformers.TransformerListener
* add some more tok2vec tests
* use select_pipes
* fix docs - annotation setter was not changed in the end
Sort the returned matches by rule order (the `match_id`) so that the
rules are applied in the order they were added. This is necessary, for
instance, if the `AttributeRuler` is used for the tag map and later
rules require POS tags.
Serialize `AttributeRuler.patterns` instead of the individual lists to
simplify the serialized and so that patterns are reloaded exactly as
they were originally provided (preserving `_attrs_unnormed`).
* Add AttributeRuler.score
Add scoring for TAG / POS / MORPH / LEMMA if these are present in the
assigned token attributes.
Add default score weights (that don't really make a lot of sense) so
that the scores are in the default config in some form.
* Update docs
* Update stop_words.py
Hebrew STOP WORDS
* Update stop_words.py
* contributor
* contributor
* add some common domain extentions
support human number 1K/1M....
* support human number 1K/1M....
* hebrew number tokenize
1K/1M implement in EN
* test human tokenize fix
* test
* heb like num
revert human number change
* heb like num
* Create lex_attrs.py
Hello,
I am missing a CZECH language in SpaCy. So I would like to help to push it a little. This file is base on others lex_attrs.py files just with translation to Czech.
* Update __init__.py
Updated for use with new Czech Lex_attrs file
* Update stop_words.py
* Create test_text.py
* add like_num testing for czech
Co-authored-by: holubvl3 <47881982+holubvl3@users.noreply.github.com>
Co-authored-by: holubvl3 <vilemrousi@gmail.com>
Co-authored-by: Vladimír Holubec <vholubec@arcdata.cz>
- Accept any case for label names in ents and colors option, even if actual predicted label uses different casing
- Don't text-transform: uppercase visually, if it's important to users that the label is represented as-is in the UI
- As much as I dislike YAML, it seemed like a better format here because it allows us to add comments if we want to explain the different recommendations
- Don't include the generated JS in the repo by default and build it on the fly when running or deploying the site. This ensures it's always up to date.
- Simplify jinja_to_js script and use fewer dependencies
* candidate generator as separate part of EL config
* update comment
* ent instead of str as input for candidate generation
* Span instead of str: correct type indication
* fix types
* unit test to create new candidate generator
* fix replace_pipe argument passing
* move error message, general cleanup
* add vocab back to KB constructor
* provide KB as callable from Vocab arg
* rename to kb_loader, fix KB serialization as part of the EL pipe
* fix typo
* reformatting
* cleanup
* fix comment
* fix wrongly duplicated code from merge conflict
* rename dump to to_disk
* from_disk instead of load_bulk
* update test after recent removal of set_morphology in tagger
* remove old doc
