Description
The T5 transformer model described in the seminal paper “Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer” can perform a variety of tasks, such as text summarization, question answering and translation. More details about using the model can be found in the paper (https://arxiv.org/pdf/1910.10683.pdf). This model is specifically trained on medical data for text summarization and question answering.
Predicted Entities
How to use
document_assembler = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("documents")
t5 = T5Transformer().pretrained("t5_base_pubmedqa", "en", "clinical/models")\
.setInputCols(["documents"])\
.setOutputCol("t5_output")\
.setTask("summarize medical questions:")\
.setMaxOutputLength(200)
pipeline = Pipeline(stages=[document_assembler, t5])
data = spark.createDataFrame([
[1, "content:SUBJECT: Normal physical traits but no period MESSAGE: I'm a 40 yr. old woman that has infantile reproductive organs and have never experienced a mensus. I have had Doctors look but they all say I just have infantile female reproductive organs. When I try to look for answers on the internet I cannot find anything. ALL my \"girly\" parts are normal. My organs never matured. Could you give me more information please. focus:all"]
]).toDF('id', 'text')
results = pipeline.fit(data).transform(data)
results.select("t5_output.result").show(truncate=False)
val document_assembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("documents")
val t5 = T5Transformer()
.pretrained("t5_base_pubmedqa", "en", "clinical/models")
.setInputCols("documents")
.setOutputCol("t5_output")
.setTask("summarize medical questions:")
.setMaxOutputLength(200)
val pipeline = new Pipeline().setStages(Array(document_assembler, t5))
val data = Seq(Array(
(1, "content:SUBJECT: Normal physical traits but no period MESSAGE: I'm a 40 yr. old woman that has infantile reproductive organs and have never experienced a mensus. I have had Doctors look but they all say I just have infantile female reproductive organs. When I try to look for answers on the internet I cannot find anything. ALL my \"girly\" parts are normal. My organs never matured. Could you give me more information please. focus:all")
)).toDF("id", "text")
val results = pipeline.fit(data).transform(data)
import nlu
nlu.load("en.t5.base_pubmedqa").predict("""content:SUBJECT: Normal physical traits but no period MESSAGE: I'm a 40 yr. old woman that has infantile reproductive organs and have never experienced a mensus. I have had Doctors look but they all say I just have infantile female reproductive organs. When I try to look for answers on the internet I cannot find anything. ALL my \""")
Results
I have a normal physical appearance and have no mensus. Can you give me more information?
Model Information
| Model Name: | t5_base_pubmedqa |
| Compatibility: | Spark NLP for Healthcare 4.1.0+ |
| License: | Licensed |
| Edition: | Official |
| Input Labels: | [documents] |
| Output Labels: | [t5] |
| Language: | en |
| Size: | 916.7 MB |
References
Trained on Pubmed data & qnli