Arabic BertForSequenceClassification Base Cased model (from CAMeL-Lab)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. bert-base-arabic-camelbert-msa-did-madar-twitter5 is a Arabic model originally trained by CAMeL-Lab.

Predicted Entities

Palestine, Egypt, United_Arab_Emirates, Somalia, Djibouti, Libya, Tunisia, Bahrain, Jordan, Sudan, Morocco, Lebanon, Saudi_Arabia, Kuwait, Mauritania, Yemen, Qatar, Iraq, Syria, Algeria, Oman

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_bert_base_arabic_camelbert_msa_did_madar_twitter5","ar") \
    .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_bert_base_arabic_camelbert_msa_did_madar_twitter5","ar")
    .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("ar.classify.bert.twitter.base").predict("""PUT YOUR STRING HERE""")

Model Information

References

• https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-did-madar-twitter5
• https://camel.abudhabi.nyu.edu/madar-shared-task-2019/
• https://arxiv.org/abs/2103.06678
• https://github.com/CAMeL-Lab/CAMeLBERT
• https://github.com/CAMeL-Lab/camel_tools