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@@ -10,13 +10,13 @@ license: mit
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  **Chuxin-1.6B-1M**是基于Chuxin-1.6B模型在1M窗口下训练后的结果,大海捞针实验显示其具有非常强的上下文检索能力。
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- 如果您想了解更多关于Chuxin-1.6B开源模型的细节,我们建议您参阅我们的[技术报告](https://xxxx)
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  **Chuxin-1.6B-Base** is a model with 1.6 billion parameters. Chuxin-1.6B is built entirely on open-source data. After being trained with large-scale data, Chuxin has very competitive capabilities in various downstream tasks.
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  **Chuxin-1.6B-1M** is the result of training the Chuxin-1.6B model with a 1M windows. Experiments such as searching for a needle in a haystack demonstrate its strong contextual retrieval abilities.
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- If you would like to learn more about the Chuxin-1.6B open-source model, we suggest you refer to our [technical report](https://xxxx).
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  <br>
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  ## 快速使用(Quickstart)
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  @article{chuxin,
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  title={CHUXIN: 1.6B TECHNICAL REPORT},
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  author={Xiaomin Zhuang, Yufan Jiang, Qiaozhi He, Zhihua Wu},
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- journal={arXiv preprint arXiv:xxx},
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  year={2024}
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  }
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  ```
 
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  **Chuxin-1.6B-1M**是基于Chuxin-1.6B模型在1M窗口下训练后的结果,大海捞针实验显示其具有非常强的上下文检索能力。
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+ 如果您想了解更多关于Chuxin-1.6B开源模型的细节,我们建议您参阅我们的[技术报告](https://arxiv.org/pdf/2405.04828)
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  **Chuxin-1.6B-Base** is a model with 1.6 billion parameters. Chuxin-1.6B is built entirely on open-source data. After being trained with large-scale data, Chuxin has very competitive capabilities in various downstream tasks.
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  **Chuxin-1.6B-1M** is the result of training the Chuxin-1.6B model with a 1M windows. Experiments such as searching for a needle in a haystack demonstrate its strong contextual retrieval abilities.
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+ If you would like to learn more about the Chuxin-1.6B open-source model, we suggest you refer to our [technical report](https://arxiv.org/pdf/2405.04828).
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  <br>
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  ## 快速使用(Quickstart)
 
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  @article{chuxin,
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  title={CHUXIN: 1.6B TECHNICAL REPORT},
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  author={Xiaomin Zhuang, Yufan Jiang, Qiaozhi He, Zhihua Wu},
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+ journal={arXiv preprint arXiv:2405.04828},
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  year={2024}
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  }
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  ```