Datasetpublic

codelion/finepdfs-100M

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 100M token sample is representative of the full dataset's characteristics. Source Dataset: HuggingFaceFW/finepdfs Sample Size: 100M tokens Content: High-quality textbook-style pdfs Reservoir sampling enables rapid experimentation and ablation… See the full description on the dataset page: https://huggingface.co/datasets/codelion/finepdfs-100M.

sourceHugging Faceupdated 11mo agoView on Hugging Face

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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 100M token sample is representative of the full dataset's characteristics.

Source Dataset: HuggingFaceFW/finepdfs Sample Size: 100M 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.

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.