English RobertaForSequenceClassification Cased model (from lucianpopa)

Description

Pretrained RobertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. autotrain-qn-classification-1015534072 is a English model originally trained by lucianpopa.

Predicted Entities

atis_airline, atis_city, atis_ground_fare, atis_flight_time, atis_flight, atis_capacity, atis_quantity, atis_flight_no, atis_airport, atis_distance, atis_flight#atis_airfare, atis_aircraft, atis_airfare, atis_abbreviation, atis_ground_service

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 = RoBertaForSequenceClassification.pretrained("roberta_classifier_autotrain_qn_classification_1015534072","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 = RoBertaForSequenceClassification.pretrained("roberta_classifier_autotrain_qn_classification_1015534072","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.qn.roberta.by_lucianpopa").predict("""PUT YOUR STRING HERE""")

Model Information

References

• https://huggingface.co/lucianpopa/autotrain-qn-classification-1015534072