Description
Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.bio_clinicalbert_for_seizurefreedom_classification_cnt_upenn_pipeline is a English model originally trained by CNT-UPenn.
How to use
pipeline = PretrainedPipeline("bio_clinicalbert_for_seizurefreedom_classification_cnt_upenn_pipeline", lang = "en")
annotations = pipeline.transform(df)
val pipeline = new PretrainedPipeline("bio_clinicalbert_for_seizurefreedom_classification_cnt_upenn_pipeline", lang = "en")
val annotations = pipeline.transform(df)
Model Information
| Model Name: | bio_clinicalbert_for_seizurefreedom_classification_cnt_upenn_pipeline |
| Type: | pipeline |
| Compatibility: | Spark NLP 5.5.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 405.3 MB |
References
https://huggingface.co/CNT-UPenn/Bio_ClinicalBERT_for_seizureFreedom_classification
Included Models
- DocumentAssembler
- TokenizerModel
- BertForSequenceClassification