English DistilBertForSequenceClassification Cased model (from Preetiha)

Description

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

Predicted Entities

Cooperation, No Conflicts, Payments, Confidentiality, Submission To Jurisdiction, Jurisdictions, Authority, Disability, Costs, Insurances, Consent To Jurisdiction, Tax Withholdings, Base Salary, Benefits, Construction, Solvency, Interpretations, Miscellaneous, Definitions, Qualifications, Liens, Erisa, Waiver Of Jury Trials, Financial Statements, Defined Terms, Integration, Modifications, Assignments, Existence, Arbitration, Successors, Applicable Laws, Venues, Specific Performance, Further Assurances, Amendments, Headings, Assigns, Non-Disparagement, Powers, Duties, Authorizations, Taxes, Counterparts, Terminations, Disclosures, Agreements, Notices, Books, Positions, Titles, Binding Effects, Change In Control, Closings, Capitalization, Entire Agreements, Representations, Compliance With Laws, Death, Anti-Corruption Laws, Litigations, Withholdings, Effective Dates, Adjustments, Approvals, Subsidiaries, General, Brokers, Severability, Remedies, Indemnifications, Indemnity, Forfeitures, Sanctions, Survival, Publicity, Vacations, Expenses, Fees, Waivers, Intellectual Property, Terms, Employment, Consents, Use Of Proceeds, Records, Governing Laws, Effectiveness, Transactions With Affiliates, Releases, Vesting, Interests, Organizations, Enforcements, Warranties, Participations, Sales, No Waivers, No Defaults, Enforceability

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_clause_classification","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_clause_classification","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)

import nlu
nlu.load("en.classify.distil_bert.by_preetiha").predict("""PUT YOUR STRING HERE""")

Model Information

References

• https://huggingface.co/Preetiha/clause_classification