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@@ -16,7 +16,7 @@ With 1.4B non-embedding parameters and training on 2.2 trillion tokens,
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  it achieves performance competitive with current state-of-the-art fully open models and even rivals some leading open-weight models of similar scale.
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  <center>
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- ![Model Performance Comparison](model_performance_comparison.svg)
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  </center>
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  We will publish the datasets used to train Kaiyuan-2B soon.
 
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  it achieves performance competitive with current state-of-the-art fully open models and even rivals some leading open-weight models of similar scale.
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  <center>
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+ <img alt="Model Performance Comparison" src="model_performance_comparison.svg"/>
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  </center>
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  We will publish the datasets used to train Kaiyuan-2B soon.