Arabic BertForSequenceClassification Base Cased model (from Abdelrahman-Rezk)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. bert-base-arabic-camelbert-mix-poetry-finetuned-qawaf is a Arabic model originally trained by Abdelrahman-Rezk.

Predicted Entities

المضارع, المتقارب, المقتضب, الهزج, السلسلة, المجتث, الطويل, عامي, الرمل, الرجز, الوافر, المتدارك, المواليا, الدوبيت, الخفيف, شعر التفعيلة, المديد, السريع, المنسرح, شعر حر, البسيط, الكامل, موشح

Live Demo Open in Colab Download Copy S3 URI

How to use

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

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

sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_base_arabic_camel_mix_poetry_finetuned_qawaf","ar") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("class")

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

data = spark.createDataFrame([["أنا أحب الشرارة NLP"]]).toDF("text")

result = pipeline.fit(data).transform(data)

val documentAssembler = new DocumentAssembler() 
          .setInputCol("text") 
          .setOutputCol("document")

val tokenizer = new Tokenizer() 
    .setInputCols(Array("document"))
    .setOutputCol("token")

val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_base_arabic_camel_mix_poetry_finetuned_qawaf","ar") 
    .setInputCols(Array("document", "token")) 
    .setOutputCol("class")

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

val data = Seq("أنا أحب الشرارة NLP").toDF("text")

val result = pipeline.fit(data).transform(data)

Model Information

References

• https://huggingface.co/Abdelrahman-Rezk/bert-base-arabic-camelbert-mix-poetry-finetuned-qawaf