Description
Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP mpnet_embeddings_biolord_2023 is a English model originally trained by FremyCompany.
Predicted Entities
How to use
document_assembler = DocumentAssembler()\
.setInputCol("text")\
.setOutputCol("documents")
embeddings =MPNetEmbeddings.pretrained("mpnet_embeddings_biolord_2023","en")\
.setInputCols(["documents"])\
.setOutputCol("mpnet_embeddings")
pipeline = Pipeline().setStages([document_assembler, embeddings])
result = pipeline.fit(data).transform(data)
val document_assembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("documents")
val embeddings = MPNetEmbeddings
.pretrained("mpnet_embeddings_biolord_2023", "en")
.setInputCols(Array("documents"))
.setOutputCol("mpnet_embeddings")
val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
val result = pipeline.fit(data).transform(data)
Model Information
| Model Name: | mpnet_embeddings_biolord_2023 |
| Compatibility: | Spark NLP 5.2.2+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [document] |
| Output Labels: | [MPNet] |
| Language: | en |
| Size: | 407.0 MB |
References
https://huggingface.co/FremyCompany/BioLORD-2023