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            </div>
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            <div align="center">
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              |<a href="https://github.com/hpcaitech/Colossal-LLaMA-2 | 
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              <a href="https://github.com/baichuan-inc/Baichuan-7B/blob/main/media/wechat.jpeg?raw=true" target="_blank">😊 Slack</a>|
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              <a href="https://github.com/baichuan-inc/Baichuan-7B/blob/main/media/wechat.jpeg?raw=true" target="_blank">💬 WeChat</a>|
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            </div>
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            In an effort to achieve a more balanced distribution and exert control over the dataset's ordering, we have adopted a method where we divide each sub-dataset into discrete bins. These bins are then combined to construct individual data buckets, with one bin contributed by each sub-dataset.
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            For more details, please refer to our [Github](https://github.com/hpcaitech/Colossal-LLaMA-2).
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            # Limitations
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            </div>
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              |<a href="https://github.com/hpcaitech/ColossalAI/tree/main/applications/Colossal-LLaMA-2" target="_blank">🔥 GitHub </a> | 
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              <a href="https://github.com/baichuan-inc/Baichuan-7B/blob/main/media/wechat.jpeg?raw=true" target="_blank">😊 Slack</a>|
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              <a href="https://github.com/baichuan-inc/Baichuan-7B/blob/main/media/wechat.jpeg?raw=true" target="_blank">💬 WeChat</a>|
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            </div>
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            In an effort to achieve a more balanced distribution and exert control over the dataset's ordering, we have adopted a method where we divide each sub-dataset into discrete bins. These bins are then combined to construct individual data buckets, with one bin contributed by each sub-dataset.
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            For more details, please refer to our [Github](https://github.com/hpcaitech/ColossalAI/tree/main/applications/Colossal-LLaMA-2).
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            # Limitations
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