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.
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