Description
BERTurk is a community-driven cased BERT model for Turkish. Some datasets used for pretraining and evaluation are contributed from the awesome Turkish NLP community, as well as the decision for the model name: BERTurk.
How to use
embeddings = BertEmbeddings.pretrained("bert_base_turkish_cased", "tr") \
.setInputCols("sentence", "token") \
.setOutputCol("embeddings")
nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, tokenizer, embeddings])
val embeddings = BertEmbeddings.pretrained("bert_base_turkish_cased", "tr")
.setInputCols("sentence", "token")
.setOutputCol("embeddings")
val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, tokenizer, embeddings))
import nlu
nlu.load("tr.embed.bert").predict("""Put your text here.""")
Model Information
| Model Name: | bert_base_turkish_cased |
| Compatibility: | Spark NLP 3.1.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [token, sentence] |
| Output Labels: | [embeddings] |
| Language: | tr |
| Case sensitive: | true |
Data Source
https://huggingface.co/dbmdz/bert-base-turkish-cased
Benchmarking
For results on PoS tagging or NER tasks, please refer to
[this repository](https://github.com/stefan-it/turkish-bert).