Chinese T5ForConditionalGeneration Base Cased model (from shibing624)

Description

Pretrained T5ForConditionalGeneration model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. mengzi-t5-base-chinese-correction is a Chinese model originally trained by shibing624.

Live Demo Open in Colab Download Copy S3 URI

How to use

documentAssembler = DocumentAssembler() \
    .setInputCols("text") \
    .setOutputCols("document")

t5 = T5Transformer.pretrained("t5_mengzi_base_chinese_correction","zh") \
    .setInputCols("document") \
    .setOutputCol("answers")
    
pipeline = Pipeline(stages=[documentAssembler, t5])

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

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

val documentAssembler = new DocumentAssembler() 
      .setInputCols("text")
      .setOutputCols("document")
       
val t5 = T5Transformer.pretrained("t5_mengzi_base_chinese_correction","zh") 
    .setInputCols("document")
    .setOutputCol("answers")
   
val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))

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

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

Model Information

References

• https://huggingface.co/shibing624/mengzi-t5-base-chinese-correction
• https://github.com/shibing624/pycorrector
• https://github.com/shibing624/pycorrector/tree/master/pycorrector/t5
• https://pan.baidu.com/s/1BV5tr9eONZCI0wERFvr0gQ
• http://nlp.ee.ncu.edu.tw/resource/csc.html
• https://github.com/wdimmy/Automatic-Corpus-Generation/blob/master/corpus/train.sgml