English DistilBertForSequenceClassification Cased model (from xInsignia)

Description

Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. autotrain-Online_orders-755323156 is a English model originally trained by xInsignia.

Predicted Entities

orderdessertintent, startorder, orderbreakfastintent, updateaddress, getseatinfo, closeaccount, replacecard, changeseatassignment, stoporder, getinformationintent, softwareupdate, checkclaimstatus, getroutingnumber, startserviceintent, getboardingpass, expensereport, transfermoney, orderchecks, getproofofinsurance, checkserverstatus, viewbillsintent, reportlostcard, checkbalance, getpromotions, reportbrokensoftware, changeorder, checkoffereligibility, orderdrinkintent, reportbrokenphone, ordersideintent, bookflight, orderpizzaintent, ordersaladintent, disputecharge, orderburgerintent, providereceipt, upgradeserviceintent

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 = DistilBertForSequenceClassification.pretrained("distilbert_sequence_classifier_autotrain_Online_orders_755323156","en") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("class")

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

data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).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 = DistilBertForSequenceClassification.pretrained("distilbert_sequence_classifier_autotrain_Online_orders_755323156","en") 
    .setInputCols(Array("document", "token")) 
    .setOutputCol("class")

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

val data = Seq("PUT YOUR STRING HERE").toDF("text")

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

Model Information

References

• https://huggingface.co/xInsignia/autotrain-Online_orders-755323156