Japanese BertForSequenceClassification Base Cased model (from kit-nlp)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. bert-base-japanese-sentiment-irony is a Japanese model originally trained by kit-nlp.

Predicted Entities

ポジティブ, ネガティブ

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_base_japanese_sentiment_irony","ja") \
    .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_base_japanese_sentiment_irony","ja")
    .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_base_japanese_sentiment_irony
Compatibility: Spark NLP 4.3.1+
License: Open Source
Edition: Official
Input Labels: [document, token]
Output Labels: [ner]
Language: ja
Size: 415.2 MB
Case sensitive: true
Max sentence length: 128

References

  • https://huggingface.co/kit-nlp/bert-base-japanese-sentiment-irony
  • http://creativecommons.org/licenses/by-sa/4.0/
  • http://creativecommons.org/licenses/by-sa/4.0/