Chinese BertForSequenceClassification Cased model (from Herais)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. pred_genre is a Chinese model originally trained by Herais.

Predicted Entities

宫廷, 科幻, 涉案, 其它, 青少, 武打, 都市, 传奇, 革命, 神话, 军旅, 农村, 传记

Download Copy S3 URI

How to use

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

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

seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_pred_genre","zh") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("class")

pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier])

data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")

result = pipeline.fit(data).transform(data)

val documentAssembler = new DocumentAssembler()
      .setInputCols(Array("text"))
      .setOutputCols(Array("document"))

val tokenizer = new Tokenizer()
    .setInputCols("document")
    .setOutputCol("token")

val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_pred_genre","zh")
    .setInputCols(Array("document", "token"))
    .setOutputCol("class")

val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier))

val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")

val result = pipeline.fit(data).transform(data)

Model Information

Model Name:	bert_classifier_pred_genre
Compatibility:	Spark NLP 4.1.0+
License:	Open Source
Edition:	Official
Input Labels:	[document, token]
Output Labels:	[class]
Language:	zh
Size:	384.1 MB
Case sensitive:	true
Max sentence length:	256

References

https://huggingface.co/Herais/pred_genre

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