Description
Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.stanford_deidentifier_with_radiology_reports_and_i2b2_pipeline is a English model originally trained by StanfordAIMI.
How to use
pipeline = PretrainedPipeline("stanford_deidentifier_with_radiology_reports_and_i2b2_pipeline", lang = "en")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("stanford_deidentifier_with_radiology_reports_and_i2b2_pipeline", lang = "en")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | stanford_deidentifier_with_radiology_reports_and_i2b2_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 408.2 MB |
References
https://huggingface.co/StanfordAIMI/stanford-deidentifier-with-radiology-reports-and-i2b2
Included Models
- DocumentAssembler
- TokenizerModel
- BertForTokenClassification