English RoBertaForSequenceClassification Cased model (from cardiffnlp)

Description

Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. tweet-topic-19-multi is a English model originally trained by cardiffnlp.

Predicted Entities

film_tv_&_video, diaries_&_daily_life, other_hobbies, music, business_&_entrepreneurs, relationships, gaming, youth_&_student_life, food_&_dining, fitness_&_health, news_&_social_concern, fashion_&_style, family, travel_&_adventure, science_&_technology, learning_&_educational, arts_&_culture, sports, celebrity_&_pop_culture

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_tweet_topic_19_multi","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_tweet_topic_19_multi","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.roberta.tweet_topic_19_multi.by_cardiffnlp").predict("""PUT YOUR STRING HERE""")

Model Information

References

References

• https://huggingface.co/cardiffnlp/tweet-topic-19-multi
• https://github.com/cardiffnlp/tweeteval
• https://arxiv.org/abs/2202.03829
• https://github.com/cardiffnlp/timelms