Description
Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. distilbert-base-dutch-cased-toxic-comments is a Dutch model originally trained by ml6team.
Predicted Entities
toxic, non-toxic
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
sequenceClassifier_loaded = DistilBertForSequenceClassification.pretrained("distilbert_sequence_classifier_distilbert_base_dutch_cased_toxic_comments","nl") \
.setInputCols(["document", "token"]) \
.setOutputCol("class")
pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded])
data = spark.createDataFrame([["Ik hou van Spark NLP"]]).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_distilbert_base_dutch_cased_toxic_comments","nl")
.setInputCols(Array("document", "token"))
.setOutputCol("class")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded))
val data = Seq("Ik hou van Spark NLP").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("nl.classify.distil_bert.cased_base").predict("""Ik hou van Spark NLP""")
Model Information
| Model Name: | distilbert_sequence_classifier_distilbert_base_dutch_cased_toxic_comments |
| Compatibility: | Spark NLP 4.1.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [document, token] |
| Output Labels: | [ner] |
| Language: | nl |
| Size: | 507.9 MB |
| Case sensitive: | true |
| Max sentence length: | 128 |
References
- https://huggingface.co/ml6team/distilbert-base-dutch-cased-toxic-comments
- https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge