English BertForSequenceClassification Cased model (from idrimadrid)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. autonlp-creator_classifications-4021083 is a English model originally trained by idrimadrid.

Predicted Entities

Star Trek, Hasbro, Disney, George R. R. Martin, NBC - Heroes, Sony Pictures, Marvel Comics, Blizzard Entertainment, Hanna-Barbera, Clive Barker, Shueisha, Matt Groening, Dreamworks, Sega, Namco, George Lucas, Stephen King, Capcom, Mortal Kombat, ABC Studios, DC Comics, South Park, Konami, Team Epic TV, J. R. R. Tolkien, Ian Fleming, IDW Publishing, Mattel, Dark Horse Comics, HarperCollins, Lego, Cartoon Network, SyFy, Universal Studios, Image Comics, Icon Comics, Wildstorm, Ubisoft, Nintendo, J. K. Rowling, Microsoft

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_autonlp_creator_classifications_4021083","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_autonlp_creator_classifications_4021083","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.by_idrimadrid").predict("""PUT YOUR STRING HERE""")

Model Information

References

• https://huggingface.co/idrimadrid/autonlp-creator_classifications-4021083