## QuRatedPajama

A 260B token subset of [cerebras/SlimPajama-627B](https://huggingface.co/datasets/cerebras/SlimPajama-627B), annotated by [princeton-nlp/QuRater-1.3B](https://huggingface.co/princeton-nlp/QuRater-1.3B/tree/main) with sequence-level quality ratings across 4 criteria:
- **Educational Value** - e.g. the text includes clear explanations, step-by-step reasoning, or questions and answers
- **Facts & Trivia** - how much factual and trivia knowledge the text contains, where specific facts and obscure trivia are preferred over more common knowledge
- **Writing Style** - how polished and good is the writing style in the text
- **Required Expertise**: - how much required expertise and prerequisite knowledge is necessary to understand the text

In a pre-processing step, we split documents in into chunks of exactly 1024 tokens. We provide tokenization with the Llama-2 tokenizer in the `input_ids` column.

**Paper:** [QuRating: Selecting High-Quality Data for Training Language Models](https://arxiv.org/pdf/2402.09739.pdf)

**Citation:**
```
@article{wettig2024qurating,
   title={QuRating: Selecting High-Quality Data for Training Language Models},
   author={Alexander Wettig, Aatmik Gupta, Saumya Malik, Danqi Chen},
   journal={arXiv preprint 2402.09739},
   year={2024}
}
```