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samandar1105/
inlegalbert-legal-ner

Name: inlegalbert-legal-ner
Availability: InStock

opennyaiorg/InLegalNER

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InLegalBERT fine-tuned for Legal Named Entity Recognition

Extracts 14 legal entity types (COURT, JUDGE, LAWYER, PETITIONER, RESPONDENT, CASE_NUMBER, STATUTE, PROVISION, PRECEDENT, WITNESS, OTHER_PERSON, ORG, GPE, DATE) from legal/court documents. Base model: law-ai/InLegalBERT (pretrained on 5.4M Indian legal documents). Fine-tuned on opennyaiorg/InLegalNER.

Performance (test set)

Metric	Score
Precision	0.8308
Recall	0.8763
F1	0.8530

Usage

python

from transformers import pipeline
ner = pipeline("token-classification", model="samandar1105/inlegalbert-legal-ner", aggregation_strategy="simple")
ner("Justice Sharma of the Bombay High Court delivered judgment on 14 March 2019.")

This model is part of a Legal NER + RAG document-intelligence pipeline (NER extraction + retrieval-augmented Q&A). See the companion Space for the full app.