--- dataset_info: features: - name: text dtype: string - name: id dtype: string - name: dump dtype: string - name: url dtype: string - name: date dtype: string - name: file_path dtype: string - name: offset dtype: int64 - name: token_count dtype: int64 - name: language dtype: string - name: page_average_lid dtype: string - name: page_average_lid_score dtype: float64 - name: full_doc_lid dtype: string - name: full_doc_lid_score dtype: float64 - name: per_page_languages list: string - name: is_truncated dtype: bool - name: extractor dtype: string - name: page_ends list: int64 splits: - name: train num_bytes: 43954704 num_examples: 7537 download_size: 24068621 dataset_size: 43954704 configs: - config_name: default data_files: - split: train path: data/train-* --- ## Sampling Methodology This dataset was created using **reservoir sampling**, a statistically unbiased random sampling algorithm that guarantees each sample from the source dataset has an equal probability of being included. This ensures the 10M token sample is representative of the full dataset's characteristics. **Source Dataset**: [HuggingFaceFW/finepdfs](https://huggingface.co/datasets/HuggingFaceFW/finepdfs) **Sample Size**: 10M tokens **Content**: High-quality textbook-style pdfs Reservoir sampling enables rapid experimentation and ablation studies without processing the entire source dataset, while maintaining statistical validity of results. For details on how this dataset was used in optimal pre-training data composition research, see the [blog post](https://huggingface.co/blog/codelion/optimal-dataset-mixing/). ## Citation If you use this model/dataset, please cite: ```bibtex @article{sharma2025billion, title={The 1 Billion Token Challenge: Finding the Perfect Pre-training Mix}, author={Sharma, Asankhaya}, year={2025}, url={https://huggingface.co/blog/codelion/optimal-dataset-mixing/} } ``` For more details, see the [blog post](https://huggingface.co/blog/codelion/optimal-dataset-mixing/).