Description
Pretrained T5ForConditionalGeneration model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. t5-base-finetuned-squadv2 is a English model originally trained by mrm8488.
How to use
documentAssembler = DocumentAssembler() \
.setInputCols("text") \
.setOutputCols("document")
t5 = T5Transformer.pretrained("t5_base_finetuned_squadv2","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_base_finetuned_squadv2","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
| Model Name: | t5_base_finetuned_squadv2 |
| Compatibility: | Spark NLP 4.3.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [documents] |
| Output Labels: | [t5] |
| Language: | en |
| Size: | 861.2 MB |
References
- https://huggingface.co/mrm8488/t5-base-finetuned-squadv2
- https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html
- https://rajpurkar.github.io/SQuAD-explorer/
- https://arxiv.org/pdf/1910.10683.pdf
- https://i.imgur.com/jVFMMWR.png
- https://colab.research.google.com/github/patil-suraj/exploring-T5/blob/master/T5_on_TPU.ipynb
- https://twitter.com/mrm8488
- https://www.linkedin.com/in/manuel-romero-cs/