Welcome to page of Turkish spaCy models. You can find all the models under our Huggingface repo. This repo contains config files for
- tr_core_web_md
- tr_core_web_lg
- tr_core_web_trf
All pipelines contains a tokenizer, trainable lemmatizer, POS tagger, dependency parser, morphologizer and NER components.
tr_core_web_lg is a CNN-based large sized model, which offers a good accuracy and works on decent speed. This model includes all the components above
and is packaged with large sized Floret word vectors.
Similarly tr_core_web_md is a CNN-based medium sized model, which achieves a decent accuracy and might be a good choice for speed-critical applications.
and is packaged with medium sized Floret word vectors.
tr_core_web_trf is a Tranformer based pipeline. It offers a great accuracy, if you have good computing resources, this is your model of choice (even better some GPUs).
You can download all the models from Huggingface:
- Transformer based model
pip install https://huggingface.co/turkish-nlp-suite/tr_core_news_trf/resolve/main/tr_core_news_trf-any-py3-none-any.whl - Large model:
pip install https://huggingface.co/turkish-nlp-suite/tr_core_news_lg/resolve/main/tr_core_news_lg-any-py3-none-any.whl - Medium model:
pip install https://huggingface.co/turkish-nlp-suite/tr_core_news_md/resolve/main/tr_core_news_md-any-py3-none-any.whl
After installing the models via pip you can directly use by loading into spaCy:
import spacy
nlp = spacy.load("tr_core_news_trf")
doc = nlp("Dün ben de gittim.")
Documentation is available on our website: [TODO]
Please visit my channel for two playlists Hızlı spaCy Türkçe tarifleri and spaCy modeli nasıl yapılır?. You'll find quick recipes with spaCy Turkish in the first playlist and the second playlist gives details of how to train&package a model for a new language.
This work is supported by Google Developer Experts Program. Part of Duygu 2022 Fall-Winter collection, "Turkish NLP with Duygu"/ "Duygu'yla Türkçe NLP". All rights reserved.