Update README.md

README.md

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 Paper: [QuRating: Selecting High-Quality Data for Training Language Models](https://arxiv.org/pdf/2402.09739.pdf)
 
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+**_Guidance on Responsible Use_**
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+In the paper, we document various types of bias that are present in the quality ratings/QuRater model (biases related to domains, topics, social roles, regions and languages - see Section 6 of the paper).
+Hence, be aware that data selection with QuRating could have unintended and harmful effects on the language model that is being trained. We strongly recommend a comprehensive evaluation of the language model for these and other types of bias, particularly before real-world deployment. We hope that releasing the data/models can facilitate future research aimed at uncovering and mitigating such biases.
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 Citation:
 ```
 @article{wettig2024qurating,