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  ## Introduction
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- Ring-lite is a fully open-source MoE LLM provided by InclusionAI, which has 16.8B parameters with 2.75B activated parameters. It is built upon the publicly available [Ling-lite-1.5](https://huggingface.co/inclusionAI/Ling-lite-1.5) model. We use a joint training pipeline combining knowledge distillation with reinforcement learning. achieving performance comparable to state-of-the-art (SOTA) small-size reasoning models on challenging benchmarks (AIME, LiveCodeBench, and GPQA-Diamond) while activating only one-third of their parameters.
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  ## Introduction
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+ Ring-lite is a lightweight, fully open-sourced MoE (Mixture of Experts) LLM designed for complex reasoning tasks. It is built upon the publicly available [Ling-lite-1.5](https://huggingface.co/inclusionAI/Ling-lite-1.5) model, which has 16.8B parameters with 2.75B activated parameters.. We use a joint training pipeline combining knowledge distillation with reinforcement learning. achieving performance comparable to state-of-the-art (SOTA) small-size reasoning models on challenging benchmarks (AIME, LiveCodeBench, and GPQA-Diamond) while activating only one-third of their parameters.
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