Hungarian models for spaCy

This repository contains the building blocks and the releases of Hungarian models for spaCy.

Releases

Date	Model	Version	spaCy	Features	Size	Memory
2019-01-04	`hu_core_ud_lg`	`0.1.0`	`>2.0.0,` `<2.1.0`	Word vectors, Brown clusters, Token frequencies, Sentencizer, PoS Tagger, Lemmatizer, Dependency parser	1.3G	2.5G
2019-06-02	`hu_core_ud_lg`	`0.2.0`	`>=2.1.0,` `<2.2.0`	Word vectors, Brown clusters, Token frequencies, Sentencizer, PoS Tagger, Lemmatizer, Dependency parser	1.3G	2.5G
2019-09-26	`hu_core_ud_lg`	`0.3.0`	`>=2.1.8,` `<2.2.0`	Word vectors, Brown clusters, Token frequencies, Sentencizer, PoS Tagger, Lemmatizer, Dependency parser, NER	1.3G	2.5G
2019-10-03	`hu_core_ud_lg`	`0.3.1`	`>=2.2.0,` `<2.3.0`	Word vectors, Brown clusters, Token frequencies, Sentencizer, PoS Tagger, Lemmatizer, Dependency parser, NER	1.3G	2.5G

pip install https://github.com/oroszgy/spacy-hungarian-models/releases/download/hu_core_ud_lg-0.3.1/hu_core_ud_lg-0.3.1-py3-none-any.whl

To load a model, import the model's package directly and call its load() method with no arguments.

import hu_core_ud_lg

nlp = hu_core_ud_lg.load()
doc = nlp('Csiribiri csiribiri zabszalma - négy csillag közt alszom ma.')

For detailed documentation and tutorials, check spaCy docs.

Issuing make all fetches all the resources needed and builds a release.

2019-10-03 Fixing compatibility issue with spaCy 2.2
2019-09-26 Added named entity recognition
2019-06-02 Made the pipeline compatible with spaCy 2.1, minor sentence segmentation improvements
2019-01-04 UD corpus based core pipeline release for spaCy 2.x
2017-06-11 Experimental model releases for spaCy 1.x