English BertForSequenceClassification Cased model (from jakelever)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. coronabert is a English model originally trained by jakelever.

Predicted Entities

Review, Imaging, Non-medical, Medical Devices, Transmission, Misinformation, Prevention, Infection Reports, Contact Tracing, Effect on Medical Specialties, Psychology, Meta-analysis, Drug Targets, Model Systems & Tools, Education, Communication, Forecasting & Modelling, Diagnostics, Healthcare Workers, Comment/Editorial, Recommendations, Non-human, Pediatrics, Immunology, Prevalence, Molecular Biology, Therapeutics, Clinical Reports, Health Policy, Vaccines, News, Inequality, Long Haul, Surveillance, Risk Factors

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How to use

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

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

seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_coronabert","en") \
    .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_coronabert","en")
    .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("en.classify.bert.cord19.").predict("""PUT YOUR STRING HERE""")

Model Information

Model Name: bert_classifier_coronabert
Compatibility: Spark NLP 4.1.0+
License: Open Source
Edition: Official
Input Labels: [document, token]
Output Labels: [class]
Language: en
Size: 411.1 MB
Case sensitive: true
Max sentence length: 256

References

  • https://huggingface.co/jakelever/coronabert
  • https://coronacentral.ai
  • https://github.com/jakelever/corona-ml
  • https://doi.org/10.1101/2020.12.21.423860