Sentence Embeddings - Biobert cased (MedNLI, onnx)

Description

This model is trained to generate contextual sentence embeddings of input sentences. It has been fine-tuned on MedNLI dataset to provide sota performance on STS and SentEval Benchmarks.

Predicted Entities

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How to use

sbiobert_embeddings = BertSentenceEmbeddings\
  .pretrained("sbiobert_base_cased_mli_onnx", "en", "clinical/models")\
  .setInputCols(["ner_chunk_doc"])\
  .setOutputCol("sbert_embeddings")

val sbiobert_embeddings = BertSentenceEmbeddings
  .pretrained("sbiobert_base_cased_mli_onnx", "en", "clinical/models")
  .setInputCols(Array("ner_chunk_doc"))
  .setOutputCol("sbert_embeddings")

Results

Gives a 768 dimensional vector representation of the sentence.

Model Information