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README.md
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@@ -27,4 +27,6 @@ The model architecture is LLaMA-1.3B and we adopt the [OpenLLaMA](https://github
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The model is pre-trained on 100B tokens of Data-Juicer's refined RedPajama and Pile.
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It achieves an average score of 33.07 over 16 HELM tasks, beating LLMs trained on original RedPajama and Pile datasets.
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For more details, please refer to our [paper](https://arxiv.org/abs/2309.02033).
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The model is pre-trained on 100B tokens of Data-Juicer's refined RedPajama and Pile.
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It achieves an average score of 33.07 over 16 HELM tasks, beating LLMs trained on original RedPajama and Pile datasets.
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For more details, please refer to our [paper](https://arxiv.org/abs/2309.02033).
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