Estonian BertForTokenClassification Cased model (from tartuNLP)

Description

Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. EstBERT_Morph_128 is a Estonian model originally trained by tartuNLP.

Predicted Entities

AdpType=Prep, VerbForm=Part, Case=Ade, PronType=Rel, Polarity=Neg, Degree=Pos, VerbForm=Inf, PronType=Ind, PronType=Tot, Case=Par, Abbr=Yes, Case=Nom, Foreign=Yes, _, PronType=Dem, NumType=Ord, Hyph=Yes, Connegative=Yes, AdpType=Post, NumType=Card, Number=Sing, VerbForm=Conv

Live Demo Open in Colab 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_est_morph_128","et") \
    .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_est_morph_128","et")
    .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

References

References

• https://huggingface.co/tartuNLP/EstBERT_Morph_128