Update README.md

README.md

@@ -3,6 +3,8 @@ pretty_name: QuRatedPajama-260B
 ---
 ## QuRatedPajama
 
+**Paper:** [QuRating: Selecting High-Quality Data for Training Language Models](https://arxiv.org/pdf/2402.09739.pdf)
+
 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
@@ -12,8 +14,6 @@ A 260B token subset of [cerebras/SlimPajama-627B](https://huggingface.co/dataset
 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)
-
 **Guidance on Responsible Use**
 
 In the paper, we document various types of bias that are present in the quality ratings (biases related to domains, topics, social roles, regions and languages - see Section 6 of the paper).