English T5ForConditionalGeneration Cased model (from lordtt13)

Description

Pretrained T5ForConditionalGeneration model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. t5-inshorts is a English model originally trained by lordtt13.

Live Demo Open in Colab Download Copy S3 URI

How to use

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

t5 = T5Transformer.pretrained("t5_inshorts","en") \
    .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_inshorts","en") 
    .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/lordtt13/t5-inshorts
• https://arxiv.org/abs/1910.10683
• https://www.kaggle.com/shashichander009/inshorts-news-data
• https://github.com/lordtt13/transformers-experiments/blob/master/Custom%20Tasks/fine-tune-t5-for-summarization.ipynb
• https://github.com/lordtt13
• https://www.linkedin.com/in/tanmay-thakur-6bb5a9154/