Indonesian Part of Speech Tagger (from w11wo)

Description

Pretrained Part of Speech model, uploaded to Hugging Face, adapted and imported into Spark NLP. indonesian-roberta-base-posp-tagger is a Indonesian model orginally trained by w11wo.

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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 = RoBertaForTokenClassification.pretrained("roberta_pos_indonesian_roberta_base_posp_tagger","id") \
    .setInputCols(["sentence", "token"]) \
    .setOutputCol("pos")

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

data = spark.createDataFrame([["Saya suka 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 = RoBertaForTokenClassification.pretrained("roberta_pos_indonesian_roberta_base_posp_tagger","id") 
    .setInputCols(Array("sentence", "token")) 
    .setOutputCol("pos")

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

val data = Seq("Saya suka Spark NLP").toDF("text")

val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("id.pos.indonesian_roberta_base_posp_tagger").predict("""Saya suka Spark NLP""")

Model Information

Model Name: roberta_pos_indonesian_roberta_base_posp_tagger
Compatibility: Spark NLP 3.4.2+
License: Open Source
Edition: Official
Input Labels: [document, token]
Output Labels: [ner]
Language: id
Size: 466.1 MB
Case sensitive: true
Max sentence length: 128

References

  • https://huggingface.co/w11wo/indonesian-roberta-base-posp-tagger
  • https://arxiv.org/abs/1907.11692
  • https://hf.co/flax-community/indonesian-roberta-base
  • https://hf.co/datasets/indonlu
  • https://w11wo.github.io/