Description
Pretrained BartTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.h2_keywordextractor is a English model originally trained by transformer3.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
seq2seq = BartTransformer.pretrained("h2_keywordextractor","en") \
.setInputCols(["documents"]) \
.setOutputCol("generation")
pipeline = Pipeline().setStages([documentAssembler, seq2seq])
data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
pipelineModel = pipeline.fit(data)
pipelineDF = pipelineModel.transform(data)
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val seq2seq = BartTransformer.pretrained("h2_keywordextractor","en")
.setInputCols(Array("documents"))
.setOutputCol("generation")
val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
val data = Seq("I love spark-nlp").toDF("text")
val pipelineModel = pipeline.fit(data)
val pipelineDF = pipelineModel.transform(data)
Model Information
| Model Name: | h2_keywordextractor |
| Compatibility: | Spark NLP 5.5.1+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [document] |
| Output Labels: | [output] |
| Language: | en |
| Size: | 1.9 GB |
References
https://huggingface.co/transformer3/H2-keywordextractor