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@@ -17,7 +17,7 @@ size_categories:
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  <img src="prox-teaser.png">
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  </p>
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- [ArXiv](http://arxiv.org/abs/xxxx) | [Models](https://huggingface.co/collections/gair-prox/prox-general-models-65f1674f0607712c4d6eec76) | [Code](https://github.com/GAIR-NLP/ProX)
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  RedPajama-pro is refined from [RedPajama-Data-V2](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-V2) using the **ProX** refining framework.
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  It contains about 30B high quality tokens, ready for general language model pre-training.
@@ -29,6 +29,10 @@ RedPajama-pro is based on RedPajama-Data-V2, which is made available under an ap
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  ### Citation
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  ```
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- @misc{TBD
 
 
 
 
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  }
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  ```
 
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  <img src="prox-teaser.png">
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  </p>
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+ [ArXiv](https://arxiv.org/abs/2409.17115) | [Models](https://huggingface.co/collections/gair-prox/prox-general-models-65f1674f0607712c4d6eec76) | [Code](https://github.com/GAIR-NLP/ProX)
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  RedPajama-pro is refined from [RedPajama-Data-V2](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-V2) using the **ProX** refining framework.
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  It contains about 30B high quality tokens, ready for general language model pre-training.
 
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  ### Citation
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  ```
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+ @article{zhou2024programming,
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+ title={Programming Every Example: Lifting Pre-training Data Quality like Experts at Scale},
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+ author={Zhou, Fan and Wang, Zengzhi and Liu, Qian and Li, Junlong and Liu, Pengfei},
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+ journal={arXiv preprint arXiv:2409.17115},
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+ year={2024}
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  }
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  ```