Description
Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. tiny-bert-master-classifier
is a English model originally trained by chatwithnerd
.
Predicted Entities
lentMoney
, queryBudget
, general
, showExpenses
, thanks
, creditCard
, goal
, howWillYouTrack
, income
, investment
, greeting
, stop
, howToEdit
, howToAddExp
, invalidInput
, help
, zeroinp
, wtf
, currentBalance
, loan
, howToAddLentMoney
, showGoal
, forgotSpend
, emojiHelp
, refund
, questions
, money
, moneyPending
, addSpend
, edit
, negative
, goodbye
, editBudgetData
, howToAddRefund
, cvtEMI
, lastBudget
, expenses
, cashATM
, insight
, incompleteSpend
, recap
, spendAdvice
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_tiny_master","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_tiny_master","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.tiny.by_chatwithnerd").predict("""PUT YOUR STRING HERE""")
Model Information
Model Name: | bert_classifier_tiny_master |
Compatibility: | Spark NLP 4.2.0+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [document, token] |
Output Labels: | [class] |
Language: | en |
Size: | 54.5 MB |
Case sensitive: | true |
Max sentence length: | 256 |
References
- https://huggingface.co/chatwithnerd/tiny-bert-master-classifier