English T5ForConditionalGeneration Small Cased model (from google)

Description

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

Predicted Entities

Live Demo Open in Colab Download Copy S3 URI

How to use

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

t5 = T5Transformer.pretrained("t5_small_ssm","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_small_ssm","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

References

• https://huggingface.co/google/t5-small-ssm
• https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html
• https://arxiv.org/pdf/2002.08909.pdf
• https://arxiv.org/abs/1910.10683.pdf
• https://goo.gle/t5-cbqa
• https://raw.githubusercontent.com/patrickvonplaten/scientific_images/master/how_much_know_ledge_image.png