Biobert Pmc Base Cased


BERT (Bidirectional Encoder Representations from Transformers) provides dense vector representations for natural language by using a deep, pre-trained neural network with the Transformer architecture. Contextual embeddings representation using biobert_pmc_base_cased.

Predicted Entities

Contextual feature vectors based on biobert_pmc_base_cased.


How to use

model = BertEmbeddings.pretrained("biobert_pmc_base_cased","en","clinical/models")\
val model = BertEmbeddings.pretrained("biobert_pmc_base_cased","en","clinical/models")

Model Information

Name: biobert_pmc_base_cased  
Type: BertEmbeddings  
Compatibility: Spark NLP 2.5.0+  
License: Licensed  
Edition: Official  
Input labels: [document, sentence, token]  
Output labels: [word_embeddings]  
Language: en  
Dimension: 768.0  
Case sensitive: True  

Data Source

Trained on PubMed + MIMIC III corpora