Text Generation
Transformers
GGUF
mistral
openchat
C-RLFT
conversational
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@@ -547,15 +547,11 @@ All models are evaluated in chat mode (e.g. with the respective conversation tem
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  *: Grok results are reported by [X.AI](https://x.ai/).
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- <div>
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- <h3>Massive Multitask Language Understanding in Chinese (CMMLU)</h3>
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- 5-shot:
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  </div>
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- | Models | STEM | Humanities | SocialSciences | Other | ChinaSpecific | Avg |
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- |----------|-------|------------|----------------|-------|---------------|-------|
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- | ChatGPT | 47.81 | 55.68 | 56.5 | 62.66 | 50.69 | 55.51 |
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- | OpenChat | 38.7 | 45.99 | 48.32 | 50.23 | 43.27 | 45.85 |
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  <div>
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  <h3>Multi-Level Multi-Discipline Chinese Evaluation Suite (CEVAL)</h3>
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  | ChatGPT | 54.4 | 52.9 | 61.8 | 50.9 | 53.6 |
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  | OpenChat | 47.29 | 45.22 | 52.49 | 48.52 | 45.08 |
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  <div align="center">
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  <h2> Limitations </h2>
 
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  *: Grok results are reported by [X.AI](https://x.ai/).
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+ <div align="center">
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+ <h2> 中文评估结果 / Chinese Evaluations </h2>
 
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+ ⚠️ Note that this model was not explicitly trained in Chinese (only < 0.1% of the data is in Chinese). 请注意本模型没有针对性训练中文(中文数据占比小于0.1%)。
 
 
 
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  <div>
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  <h3>Multi-Level Multi-Discipline Chinese Evaluation Suite (CEVAL)</h3>
 
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  | ChatGPT | 54.4 | 52.9 | 61.8 | 50.9 | 53.6 |
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  | OpenChat | 47.29 | 45.22 | 52.49 | 48.52 | 45.08 |
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+ <div>
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+ <h3>Massive Multitask Language Understanding in Chinese (CMMLU, 5-shot)</h3>
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+ </div>
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+
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+ | Models | STEM | Humanities | SocialSciences | Other | ChinaSpecific | Avg |
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+ |----------|-------|------------|----------------|-------|---------------|-------|
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+ | ChatGPT | 47.81 | 55.68 | 56.5 | 62.66 | 50.69 | 55.51 |
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+ | OpenChat | 38.7 | 45.99 | 48.32 | 50.23 | 43.27 | 45.85 |
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  <div align="center">
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  <h2> Limitations </h2>