Spanish RobertaForTokenClassification Base Cased model (from bertin-project)

Description

Pretrained RobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. bertin-base-ner-conll2002-es is a Spanish model originally trained by bertin-project.

Predicted Entities

MISC, LOC, PER, ORG

Download Copy S3 URI

How to use

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

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

tokenClassifier = RobertaForTokenClassification.pretrained("roberta_token_classifier_bertin_base_ner_conll2002","es") \
    .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 = RobertaForTokenClassification.pretrained("roberta_token_classifier_bertin_base_ner_conll2002","es")
    .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

Model Name:	roberta_token_classifier_bertin_base_ner_conll2002
Compatibility:	Spark NLP 5.2.1+
License:	Open Source
Edition:	Official
Input Labels:	[document, token]
Output Labels:	[ner]
Language:	es
Size:	425.6 MB
Case sensitive:	true
Max sentence length:	128

References

https://huggingface.co/bertin-project/bertin-base-ner-conll2002-es

PREVIOUSMongolian RobertaForTokenClassification Base Cased model (from onon214)

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