Description
The BGE embedding model was trained on a mix of different datasets. We used public data and in-house annotated documents.
Predicted Entities
How to use
embeddings = nlp.BGEEmbeddings.pretrained("legal_bge_base_embeddings","en","legal/models")\
.setInputCols("document")\
.setOutputCol("embeddings")
Model Information
Model Name: | legal_bge_base_embeddings |
Compatibility: | Legal NLP 1.0.0+ |
License: | Licensed |
Edition: | Official |
Input Labels: | [document] |
Output Labels: | [sentence_embeddings] |
Language: | en |
Size: | 394.4 MB |
References
Public data and in-house annotated documents