A 150M model that extracts verbatim evidence spans for RAG, no LLM call

What it does

Model Name: verbatim-rag-modern-bert-v2 Organization: KRLabsOrg Github: https://github.com/KRLabsOrg/verbatim-rag The Verbatim-RAG Extractor is a query-conditioned token classifier that highlights the verbatim spans of a passage that answer a question. It is the encoder companion to VerbatimRAG and the successor to verbatim-rag-modern-bert-v1 . Built on Alibaba-NLP/gte-reranker-modernbert-base , which provides the long ModernBERT context (up to 8192 tokens) and a query-conditioned reranking prior on top of which span extraction is fine-tuned. The goal is a lightweight extractor that can replace many LLM-based evidence highlighting calls in production RAG systems: local, deterministic, cheap…from huggingface.co

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