Description
Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. autotrain-mbtiNlp-798824628
is a English model originally trained by Sathira
.
Predicted Entities
INTJ
, ENTP
, ESTJ
, ESFJ
, ESFP
, ENFP
, INFJ
, ENTJ
, ISFJ
, ISTP
, ENFJ
, ISTJ
, INFP
, ISFP
, INTP
, ESTP
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
sequenceClassifier_loaded = DistilBertForSequenceClassification.pretrained("distilbert_sequence_classifier_autotrain_mbtiNlp_798824628","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_autotrain_mbtiNlp_798824628","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)
Model Information
Model Name: | distilbert_sequence_classifier_autotrain_mbtiNlp_798824628 |
Compatibility: | Spark NLP 4.1.0+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [document, token] |
Output Labels: | [ner] |
Language: | en |
Size: | 249.8 MB |
Case sensitive: | true |
Max sentence length: | 128 |
References
- https://huggingface.co/Sathira/autotrain-mbtiNlp-798824628