Description
Pretrained mpnet model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.mpnet_embedding_java_usage_classifier is a English model originally trained by AISE-TUDelft.
How to use
document_assembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("documents")
instruction = MPNetEmbeddings \
.pretrained("mpnet_embedding_java_usage_classifier", "en")\
.setInputCols(["documents"]) \
.setOutputCol("mpnet_embeddings")
pipeline = Pipeline(stages=[
document_assembler,
instruction,
])
pipelineModel = pipeline.fit(data)
pipelineDF = pipelineModel.transform(data)
val document_assembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("documents")
val instruction = MPNetEmbeddings
.pretrained("mpnet_embedding_java_usage_classifier", "en")
.setInputCols(Array("documents"))
.setOutputCol("mpnet_embeddings")
val pipeline = new Pipeline().setStages(Array(document_assembler, instruction))
val pipelineModel = pipeline.fit(data)
val pipelineDF = pipelineModel.transform(data)
Model Information
| Model Name: | mpnet_embedding_java_usage_classifier |
| Compatibility: | Spark NLP 5.1.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [documents] |
| Output Labels: | [mpnet_embeddings] |
| Language: | en |
| Size: | 409.9 MB |