Spanish ElectraForSequenceClassification Base Cased model (from mrm8488)

Description

Pretrained ElectraForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. electricidad-base-finetuned-go_emotions-es is a Spanish model originally trained by mrm8488.

Predicted Entities

asco, deseo, remordimiento, aprobación, gratitud, enfado, neutral, alivio, realización, molestia, dolor, sorpresa, miedo, orgullo, decepción, admiración, amor, diversión, alegría, desaprobación, cuidando, curiosidad, vergüenza, excitación, optimismo, nerviosismo, confusión, tristeza

Download Copy S3 URI

How to use

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

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

seq_classifier = BertForSequenceClassification.pretrained("electra_classifier_electricidad_base_finetuned_go_emotions","es") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("class")

pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier])

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 seq_classifier = BertForSequenceClassification.pretrained("electra_classifier_electricidad_base_finetuned_go_emotions","es")
    .setInputCols(Array("document", "token"))
    .setOutputCol("class")

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

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

val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("es.classify.electra.go_emotions.base_finetuned").predict("""PUT YOUR STRING HERE""")

Model Information

Model Name: electra_classifier_electricidad_base_finetuned_go_emotions
Compatibility: Spark NLP 5.1.4+
License: Open Source
Edition: Official
Input Labels: [document, token]
Output Labels: [class]
Language: es
Size: 410.6 MB
Case sensitive: true
Max sentence length: 256

References

References

  • https://huggingface.co/mrm8488/electricidad-base-finetuned-go_emotions-es
  • https://paperswithcode.com/sota?task=Text+Classification&dataset=go_emotions-es-mt