Description
Pretrained Legal BERT Sentence Embedding model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. legalevalrr is a English model originally trained by simplexico.
How to use
sent_embeddings = BertSentenceEmbeddings.pretrained("sent_bert_legalevalrr", "en") \
.setInputCols("sentence") \
.setOutputCol("bert_sentence")
nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, sent_embeddings ])
result = pipeline.fit(data).transform(data)
vval sent_embeddings = BertSentenceEmbeddings.pretrained("sent_bert_legalevalrr", "en")
.setInputCols("sentence")
.setOutputCol("bert_sentence")
val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, sent_embeddings ))
Model Information
| Model Name: | sent_bert_legalevalrr |
| Compatibility: | Spark NLP 4.3.2+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [sentence] |
| Output Labels: | [bert_sentence] |
| Language: | en |
| Size: | 409.1 MB |
| Case sensitive: | true |
References
- https://huggingface.co/simplexico/legalevalrr
- https://www.SBERT.net
- https://seb.sbert.net?model_name=%7BMODEL_NAME%7D