Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-Ranking
Paper • 2405.07920 • Published • 3
This model was introduced in the paper Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-Ranking.
For code, examples and more, please visit https://github.com/webis-de/msmarco-llm-distillation.
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#install from https://github.com/webis-de/lightning-ir from lightning_ir import CrossEncoderModule model = CrossEncoderModule("webis/monoelectra-base") model.score("query", ["doc1", "doc2", "doc3"])