Norwegian BertForSequenceClassification Base Cased model (from NbAiLab)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. nb-bert-base-mnli is a Norwegian model originally trained by NbAiLab.

Predicted Entities

neutral, contradiction, entailment

Download Copy S3 URI

How to use

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

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

sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_nb_base_mnli","no") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("class")

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

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 sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_nb_base_mnli","no")
    .setInputCols(Array("document", "token"))
    .setOutputCol("ner")

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

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

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

Model Information

Model Name: bert_sequence_classifier_nb_base_mnli
Compatibility: Spark NLP 4.3.1+
License: Open Source
Edition: Official
Input Labels: [document, token]
Output Labels: [ner]
Language: no
Size: 668.9 MB
Case sensitive: true
Max sentence length: 128

References

  • https://huggingface.co/NbAiLab/nb-bert-base-mnli
  • https://arxiv.org/abs/1909.00161
  • https://colab.research.google.com/gist/peregilk/769b5150a2f807219ab8f15dd11ea449/nbailab-mnli-norwegian-demo.ipynb
  • https://github.com/NBAiLab/notram