Description
Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.nli_mpnet_base_v2 is a English model originally trained by sentence-transformers.
Predicted Entities
How to use
document_assembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("documents")
embeddings =MPNetEmbeddings.pretrained("nli_mpnet_base_v2","en") \
.setInputCols(["documents"]) \
.setOutputCol("mpnet_embeddings")
pipeline = Pipeline().setStages([document_assembler, embeddings])
pipelineModel = pipeline.fit(data)
pipelineDF = pipelineModel.transform(data)
val document_assembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("documents")
val embeddings = MPNetEmbeddings
.pretrained("nli_mpnet_base_v2", "en")
.setInputCols(Array("documents"))
.setOutputCol("mpnet_embeddings")
val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
val pipelineModel = pipeline.fit(data)
val pipelineDF = pipelineModel.transform(data)
Model Information
| Model Name: | nli_mpnet_base_v2 |
| Compatibility: | Spark NLP 5.5.1+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [document] |
| Output Labels: | [mpnet] |
| Language: | en |
| Size: | 405.4 MB |
References
References
https://huggingface.co/sentence-transformers/nli-mpnet-base-v2