German BertForSequenceClassification Large Cased model (from dbb)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. gbert-large-jobad-classification-34 is a German model originally trained by dbb.

Predicted Entities

hr/recruiting, chem. pharm. ausbildung, vertrieb/kundenbetreuung, kaufm. studium, beschaffung/supply chain, med. tech. beruf, it studium, log. ausbildung, it ausbildung, it, med. ausbildung, pflege/therapie, tech. ausbildung, logistik/transport, gastro. touri. ausbildung, bildung/soziales, administration/sekretariat, kaufm. ausbildung, controlling/finanzen, labor/forschung, indust. produktion, chem. pharm. beruf, rettungsdienst/sicherheit, recht/justiz, med. verwaltung, quali. kontr./-management, marketing/kommunikation, tech. studium, gastro./tourismus, indust. konstruk./ingenieur, mechaniker/techniker/elektriker, arzt, hausverw./-bewirt., baugewerbe/-ingenieur

Live Demo Open in Colab Download Copy S3 URI

How to use

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

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

seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_gbert_large_jobad_classification_34","de") \
    .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("bert_classifier_gbert_large_jobad_classification_34","de")
    .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("de.classify.bert.large").predict("""PUT YOUR STRING HERE""")

Model Information

References

• https://huggingface.co/dbb/gbert-large-jobad-classification-34