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FineFreq: A Multilingual Character Frequency Dataset from Web-Scale Text

arXiv 2512.09701 ↗First posted 10 Dec 2025cs.CLcited by 0

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Abstract (arXiv)

We present FineFreq, a large-scale multilingual character frequency dataset derived from the FineWeb and FineWeb2 corpora, covering over 1900 languages and spanning 2013-2025. The dataset contains frequency counts for 96 trillion characters processed from 57 TB of compressed text. For each language, FineFreq provides per-character statistics with aggregate and year-level frequencies, allowing fine-grained temporal analysis. The dataset preserves naturally occurring multilingual features such as cross-script borrowings, emoji, and acronyms without applying artificial filtering. Each character entry includes Unicode metadata (category, script, block), enabling domain-specific or other downstream filtering and analysis. The full dataset is released in both CSV and Parquet formats, with associated metadata, available on GitHub and HuggingFace. https://github.com/Bin-2/FineFreq

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References · 6

  1. 2024The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scalecited by 1,104
  2. 2023The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Onlycited by 755
  3. 2021Challenges in Detoxifying Language Modelscited by 169
  4. 2025FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Languagecited by 134
  5. 2025Learning to Align: Addressing Character Frequency Distribution Shifts in Handwritten Text Recognitioncited by 1
  6. 2025Training Kindai OCR with parallel textline images and self-attention feature distance-based losscited by 1

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