Danish BertForTokenClassification Cased model (from DaNLP)

Description

Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. da-bert-ner is a Danish model originally trained by DaNLP.

Predicted Entities

PER, ORG, LOC, MISC

Download Copy S3 URI

How to use

documentAssembler = DocumentAssembler() \
        .setInputCol("text") \
        .setOutputCol("document")

sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
       .setInputCols(["document"])\
       .setOutputCol("sentence")

tokenizer = Tokenizer() \
    .setInputCols("sentence") \
    .setOutputCol("token")

tokenClassifier = BertForTokenClassification.pretrained("bert_ner_da_bert_ner","da") \
    .setInputCols(["sentence", "token"]) \
    .setOutputCol("ner")

pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier])

data = spark.createDataFrame([["Jeg elsker Spark NLP"]]).toDF("text")

result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler() 
          .setInputCol("text") 
          .setOutputCol("document")

val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
       .setInputCols(Array("document"))
       .setOutputCol("sentence")

val tokenizer = new Tokenizer() 
    .setInputCols(Array("sentence"))
    .setOutputCol("token")

val tokenClassifier = BertForTokenClassification.pretrained("bert_ner_da_bert_ner","da") 
    .setInputCols(Array("sentence", "token")) 
    .setOutputCol("ner")

val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier))

val data = Seq("Jeg elsker Spark NLP").toDF("text")

val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("da.ner.bert").predict("""Jeg elsker Spark NLP""")

Model Information

Model Name: bert_ner_da_bert_ner
Compatibility: Spark NLP 4.1.0+
License: Open Source
Edition: Official
Input Labels: [document, token]
Output Labels: [ner]
Language: da
Size: 412.9 MB
Case sensitive: true
Max sentence length: 128

References

  • https://huggingface.co/DaNLP/da-bert-ner
  • https://danlp-alexandra.readthedocs.io/en/latest/docs/tasks/ner.html#bert
  • https://danlp-alexandra.readthedocs.io/en/latest/docs/datasets.html#dane
  • https://github.com/certainlyio/nordic_bert