Danish BertForTokenClassification Base Cased model (from alexandrainst)

Description

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

Predicted Entities

LOC, ORG, PER, MISC

Download Copy S3 URI

How to use

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

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

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

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

data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")

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

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

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

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

val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")

val result = pipeline.fit(data).transform(data)

Model Information

Model Name: bert_token_classifier_da_ner_base
Compatibility: Spark NLP 4.3.1+
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/alexandrainst/da-ner-base
  • https://github.com/certainlyio/nordic_bert
  • https://danlp-alexandra.readthedocs.io/en/latest/docs/tasks/ner.html#bert
  • https://danlp-alexandra.readthedocs.io/en/latest/docs/datasets.html#dane