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README.md
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@@ -40,7 +40,7 @@ Apart from that, one can also use PairRM to further align instruction-tuned LLMs
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Unlike the other RMs that encode and score each candidate respectively,
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PairRM takes a pair of candidates and compares them side-by-side to indentify the subtle differences between them.
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Also, PairRM is based on [`microsoft/deberta-v3-large`](https://huggingface.co/microsoft/deberta-v3-large), and thus it is super efficient: 0.4B
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We trained PairRM on a diverse collection of six human-preference datasets (see more [here](https://huggingface.co/llm-blender/PairRM#training-datasets)).
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PairRM is part of the LLM-Blender project (ACL 2023). Please see our [paper](https://arxiv.org/abs/2306.02561) above to know more.
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Unlike the other RMs that encode and score each candidate respectively,
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PairRM takes a pair of candidates and compares them side-by-side to indentify the subtle differences between them.
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Also, PairRM is based on [`microsoft/deberta-v3-large`](https://huggingface.co/microsoft/deberta-v3-large), and thus it is super efficient: **0.4B**.
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We trained PairRM on a diverse collection of six human-preference datasets (see more [here](https://huggingface.co/llm-blender/PairRM#training-datasets)).
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PairRM is part of the LLM-Blender project (ACL 2023). Please see our [paper](https://arxiv.org/abs/2306.02561) above to know more.
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