Indonesian XLMRobertaForTokenClassification Large Cased model (from cahya)

Description

Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. xlm-roberta-large-indonesian-NER is a Indonesian model originally trained by cahya.

Predicted Entities

QTY, WOA, REG, PER, PRC, LOC, ORD, MON, GPE, DAT, LAW, CRD, EVT, ORG, LAN, FAC, TIM, PRD, NOR

Download Copy S3 URI

How to use

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

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

token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_large_indonesian","id") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("ner")

ner_converter = NerConverter()\
    .setInputCols(["document", "token", "ner"])\
    .setOutputCol("ner_chunk")

pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])

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

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

val documentAssembler = new DocumentAssembler()
      .setInputCols(Array("text"))
      .setOutputCols(Array("document"))

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

val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_large_indonesian","id")
    .setInputCols(Array("document", "token"))
    .setOutputCol("ner")

val ner_converter = new NerConverter()
    .setInputCols(Array("document", "token', "ner"))
    .setOutputCol("ner_chunk")

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

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

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

import nlu
nlu.load("id.ner.xlmr_roberta.large").predict("""PUT YOUR STRING HERE""")

Model Information

Model Name:	xlmroberta_ner_large_indonesian
Compatibility:	Spark NLP 4.1.0+
License:	Open Source
Edition:	Official
Input Labels:	[document, token]
Output Labels:	[ner]
Language:	id
Size:	1.8 GB
Case sensitive:	true
Max sentence length:	256

References

https://huggingface.co/cahya/xlm-roberta-large-indonesian-NER

PREVIOUSMultilingual XLMRobertaForTokenClassification Large Cased model

NEXTEnglish XLMRobertaForTokenClassification Large Cased model (from tner)