Description
This model contains a pre-trained weights of ClinicalBERT for discharge summaries. This domain-specific model has performance improvements on 3/5 clinical NLP tasks andd establishing a new state-of-the-art on the MedNLI dataset. The details are described in the paper “Publicly Available Clinical BERT Embeddings”.
How to use
embeddings = BertEmbeddings.pretrained("biobert_discharge_base_cased", "en") \
.setInputCols("sentence", "token") \
.setOutputCol("embeddings")
val embeddings = BertEmbeddings.pretrained("biobert_discharge_base_cased", "en")
.setInputCols("sentence", "token")
.setOutputCol("embeddings")
Model Information
| Model Name: | biobert_discharge_base_cased |
| Type: | embeddings |
| Compatibility: | Spark NLP 2.6.2 |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [sentence, token] |
| Output Labels: | [word_embeddings] |
| Language: | [en] |
| Dimension: | 768 |
| Case sensitive: | true |
Data Source
The model is imported from https://github.com/EmilyAlsentzer/clinicalBERT