Catalan RoBertaForSequenceClassification Base Cased model (from JonatanGk)

Description

Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. roberta-base-ca-finetuned-tecla is a Catalan model originally trained by JonatanGk.

Predicted Entities

Salut, Món, Unió_Europea, Govern, Educació, Mobilitat, Successos, Meteorologia, Lletres, Trànsit, Cinema, Cultura, Govern_espanyol, Música, Comerç, Empresa, Economia, Infraestructures, Societat, Festa_i_cultura_popular, Política, Policial, Medi_ambient, Judicial, Turisme, Teatre, Parlament, Partits, Treball, Equipaments_i_patrimoni

Download Copy S3 URI

How to use

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

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

seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_base_ca_finetuned_tecla","ca") \
    .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 = RoBertaForSequenceClassification.pretrained("roberta_classifier_base_ca_finetuned_tecla","ca")
    .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("ca.classify.roberta.base_finetuned.by_jonatangk").predict("""PUT YOUR STRING HERE""")

Model Information

Model Name: roberta_classifier_base_ca_finetuned_tecla
Compatibility: Spark NLP 4.1.0+
License: Open Source
Edition: Official
Input Labels: [document, token]
Output Labels: [class]
Language: ca
Size: 471.4 MB
Case sensitive: true
Max sentence length: 256

References

  • https://huggingface.co/JonatanGk/roberta-base-ca-finetuned-tecla
  • https://paperswithcode.com/sota?task=Text+Classification&dataset=tecla