English esmlmt62_2500_pipeline pipeline BertEmbeddings from hjkim811

Description

Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.esmlmt62_2500_pipeline is a English model originally trained by hjkim811.

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How to use


pipeline = PretrainedPipeline("esmlmt62_2500_pipeline", lang = "en")
annotations =  pipeline.transform(df)   


val pipeline = new PretrainedPipeline("esmlmt62_2500_pipeline", lang = "en")
val annotations = pipeline.transform(df)

Model Information

Model Name: esmlmt62_2500_pipeline
Type: pipeline
Compatibility: Spark NLP 5.5.0+
License: Open Source
Edition: Official
Language: en
Size: 407.2 MB

References

https://huggingface.co/hjkim811/esmlmt62-2500

Included Models

  • DocumentAssembler
  • TokenizerModel
  • BertEmbeddings