Spanish BertForSequenceClassification Cased model (from gabitoo1234)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. autotrain-mut_all_text-680820343 is a Spanish model originally trained by gabitoo1234.

Predicted Entities

523.0, 232.0, 192.0, 526.0, 262.0, 422.0, 330.0, 131.0, 539.0, 424.0, 342.0, 234.2, 513.0, 423.0, 234.3, 380.0, 240.0, 159.0, 521.0, 325.0, 234.1, 429.0, 234.4, 236.0, 212.0, 142.0, 449.0, 234.0, 370.0, 519.0, 512.0, 252.0, 690.0, 222.0, 529.0, 151.0, 313.0, 239.0, 361.0, 511.0, 410.0, 149.0, 390.0, 321.0, 193.0, 199.0, 611.0, 231.0, 314.0, 319.0, 490.0, 362.0, 191.0, 129.0, 235.0, 350.0, 251.0

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_autotrain_mut_all_text_680820343","es") \
    .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_autotrain_mut_all_text_680820343","es")
    .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_autotrain_mut_all_text_680820343
Compatibility: Spark NLP 5.1.4+
License: Open Source
Edition: Official
Input Labels: [document, token]
Output Labels: [ner]
Language: es
Size: 412.0 MB
Case sensitive: true
Max sentence length: 128

References

References

  • https://huggingface.co/gabitoo1234/autotrain-mut_all_text-680820343