Description
Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.biomednlp_biomedbert_base_uncased_abstract_pipeline is a English model originally trained by microsoft.
How to use
pipeline = PretrainedPipeline("biomednlp_biomedbert_base_uncased_abstract_pipeline", lang = "en")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("biomednlp_biomedbert_base_uncased_abstract_pipeline", lang = "en")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | biomednlp_biomedbert_base_uncased_abstract_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 408.1 MB |
References
https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
Included Models
- DocumentAssembler
- TokenizerModel
- BertEmbeddings