English BertForSequenceClassification Base Cased model (from jhonparra18)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. bert-base-cased-cv-studio_name-medium is a English model originally trained by jhonparra18.

Predicted Entities

Salesforce, Agile Delivery, Design, Business Hacking, Cloud Ops, Staff Generic, others, Quality Engineering, Generic, Scalable Platforms, Data and AI, Enterprise Apps, Gaming, Process Optimization, Product Acceleration, Digital eXperience Platforms, UI Engineering, Digital Marketing

Download Copy S3 URI

How to use

documentAssembler = DocumentAssembler() \
        .setInputCol("text") \
        .setOutputCol("document")

tokenizer = Tokenizer() \
    .setInputCols("document") \
    .setOutputCol("token")

sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_base_cased_cv_studio_name_medium","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 = BertForSequenceClassification.pretrained("bert_classifier_base_cased_cv_studio_name_medium","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.bert.cased_base_medium").predict("""PUT YOUR STRING HERE""")

Model Information

Model Name: bert_classifier_base_cased_cv_studio_name_medium
Compatibility: Spark NLP 4.2.0+
License: Open Source
Edition: Official
Input Labels: [document, token]
Output Labels: [class]
Language: en
Size: 406.5 MB
Case sensitive: true
Max sentence length: 256

References

  • https://huggingface.co/jhonparra18/bert-base-cased-cv-studio_name-medium