REARANK: Reasoning Re-ranking Agent via Reinforcement Learning
Paper • 2505.20046 • Published • 18
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This is a reasoning reranking agent model built upon Qwen-2.5-7B for the paper REARANK: Reasoning Re-ranking Agent via Reinforcement Learning. The model is trained on reranking dataset built from only 179 queries using GRPO to perform reranking task, the codebase is at https://github.com/lezhang7/Rearank
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# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("le723z/Rearank-7B") model = AutoModelForCausalLM.from_pretrained("le723z/Rearank-7B")