Italian BertForSequenceClassification Cased model (from mgrella)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. autonlp-bank-transaction-classification-5521155 is a Italian model originally trained by mgrella.

Predicted Entities

Category.PROFITS_PROFITS, Category.TRAVELS_TRANSPORTATION_TOLLS, Category.HEALTH_WELLNESS_WELLNESS_RELAX, Category.TRAVELS_TRANSPORTATION_HOTELS, Category.TAXES_SERVICES_PROFIT_DEDUCTION, Category.SHOPPING_OTHER, Category.HOUSING_FAMILY_VETERINARY, Category.WAGES_PROFESSIONAL_COMPENSATION, Category.TRAVELS_TRANSPORTATION_PARKING_URBAN_TRANSPORTS, Category.SHOPPING_HTECH, Category.EATING_OUT_OTHER, Category.TRAVELS_TRANSPORTATION_OTHER, Category.LEISURE_BOOKS, Category.LEISURE_CINEMA, Category.TAXES_SERVICES_BANK_FEES, Category.TAXES_SERVICES_DEFAULT_PAYMENTS, Category.TAXES_SERVICES_PROFESSIONAL_ACTIVITY, Category.SHOPPING_SPORT_ARTICLES, Category.HOUSING_FAMILY_OTHER, Category.BILLS_SUBSCRIPTIONS_OTHER, Category.MORTGAGES_LOANS_MORTGAGES, Category.TRAVELS_TRANSPORTATION_TRAVELS_HOLIDAYS, Category.LEISURE_SPORT_EVENTS, Category.HEALTH_WELLNESS_MEDICAL_EXPENSES, Category.BILLS_SUBSCRIPTIONS_BILLS, Category.HEALTH_WELLNESS_AID_EXPENSES, Category.TRAVELS_TRANSPORTATION_TAXIS, Category.TAXES_SERVICES_MONEY_ORDERS, Category.WAGES_PENSION, Category.HOUSING_FAMILY_GROCERIES, Category.CREDIT_CARDS_CREDIT_CARDS, Category.BILLS_SUBSCRIPTIONS_INTERNET_PHONE, Category.TRANSFERS_RENT_INCOMES, Category.TRAVELS_TRANSPORTATION_FUEL, Category.HOUSING_FAMILY_CHILDHOOD, Category.OTHER_CASH, Category.SHOPPING_ACCESSORIZE, Category.TRAVELS_TRANSPORTATION_BUSES, Category.EATING_OUT_COFFEE_SHOPS, Category.EATING_OUT_TAKEAWAY_RESTAURANTS, Category.WAGES_SALARY, Category.HEALTH_WELLNESS_DRUGS, Category.TRANSFERS_BANK_TRANSFERS, Category.HOUSING_FAMILY_RENTS, Category.TRAVELS_TRANSPORTATION_VEHICLE_MAINTENANCE, Category.HOUSING_FAMILY_APPLIANCES, Category.HOUSING_FAMILY_FURNITURE, Category.LEISURE_MAGAZINES_NEWSPAPERS, Category.BILLS_SUBSCRIPTIONS_SUBSCRIPTIONS, Category.HOUSING_FAMILY_MAINTENANCE_RENOVATION, Category.HOUSING_FAMILY_SERVANTS, Category.TRANSFERS_GIFTS_DONATIONS, Category.TRANSFERS_INVESTMENTS, Category.LEISURE_GAMBLING, Category.LEISURE_OTHER, Category.TRANSFERS_REFUNDS, Category.EATING_OUT_RESTAURANTS, Category.TRAVELS_TRANSPORTATION_FLIGHTS, Category.OTHER_OTHER, Category.LEISURE_CLUASSOCIATIONS, Category.MORTGAGES_LOANS_LOANS, Category.TRAVELS_TRANSPORTATION_TRAINS, Category.HEALTH_WELLNESS_OTHER, Category.TRANSFERS_SAVINGS, Category.TAXES_SERVICES_TAXES, Category.LEISURE_VIDEOGAMES, Category.TAXES_SERVICES_OTHER, Category.HEALTH_WELLNESS_GYMS, Category.OTHER_CHECKS, Category.TRANSFERS_OTHER, Category.SHOPPING_CLOTHING, Category.LEISURE_MOVIES_MUSICS, Category.TRAVELS_TRANSPORTATION_CAR_RENTAL, Category.LEISURE_THEATERS_CONCERTS, Category.SHOPPING_FOOTWEAR, Category.HOUSING_FAMILY_INSURANCES

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_bank_transaction_classification_5521155","it") \
    .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_bank_transaction_classification_5521155","it")
    .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("it.classify.bert").predict("""PUT YOUR STRING HERE""")

Model Information

References

References

• https://huggingface.co/mgrella/autonlp-bank-transaction-classification-5521155