BioBERT Pubmed

Description

This model contains a pre-trained weights of BioBERT, a language representation model for biomedical domain, especially designed for biomedical text mining tasks such as biomedical named entity recognition, relation extraction, question answering, etc. The details are described in the paper “BioBERT: a pre-trained biomedical language representation model for biomedical text mining”.

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How to use


embeddings = BertSentenceEmbeddings.pretrained("sent_biobert_pubmed_base_cased", "en") \
      .setInputCols("sentence") \
      .setOutputCol("sentence_embeddings")

val embeddings = BertSentenceEmbeddings.pretrained("sent_biobert_pubmed_base_cased", "en")
      .setInputCols("sentence")
      .setOutputCol("sentence_embeddings")

Model Information

Model Name: sent_biobert_pubmed_base_cased
Type: embeddings
Compatibility: Spark NLP 2.6.2
License: Open Source
Edition: Official
Input Labels: [sentence]
Output Labels: [sentence_embeddings]
Language: [en]
Dimension: 768
Case sensitive: true

Data Source

The model is imported from https://github.com/dmis-lab/biobert