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