---
license: odc-by
pretty_name: FineWeb-CLaR-region
size_categories:
- n>1T
tags:
- fineweb
- region-attribution
- multilingual
- web-corpus
configs:
- config_name: default
  data_files:
  - split: train
    path: data/*/*/*.parquet
---

# FineWeb-CLaR-region: region-attributed index of the multilingual web

A **region-attributed document index** over [FineWeb](https://huggingface.co/datasets/HuggingFaceFW/fineweb) and [FineWeb-2](https://huggingface.co/datasets/HuggingFaceFW/fineweb-2): **7,916,767,586 documents** across **6,332 locales** (language–script–region combinations; 346 languages). Each row is a *pointer* — document id, CommonCrawl dump, URL, and region-attribution metadata — **not the text itself**. Text is joined back from the origin corpora by document id (code below).

For a ready-to-use annotated subset **with text** (≤10,000 docs/locale, topic + cultural-taxonomy labels), see [Yusser/FineWeb-CLaR-culture](https://huggingface.co/datasets/Yusser/FineWeb-CLaR-culture).

## Layout

Hive-partitioned parquet, one directory per locale:

```
data/language_script=deu_Latn/region=MD/fineweb2-part-0000.parquet
```

## Columns

| column | type | description |
|---|---|---|
| `id` | str | origin document id (`<urn:uuid:...>`), the join key into FineWeb / FineWeb-2 |
| `dump` | str | CommonCrawl dump, e.g. `CC-MAIN-2022-05` |
| `url`, `date`, `file_path` | str | source URL, crawl date, CC WARC path |
| `language`, `language_script` | str | language code / `<lang>_<Script>` |
| `language_score` | float | origin language-id confidence |
| `token_count`, `minhash_cluster_size`, `top_langs` | | origin corpus metadata (may be null) |
| `region`, `locale` | str | attributed region code and `<lang>_<Script>-<REGION>` |
| `region_source`, `region_confidence`, `region_top_rule` | str | which attribution signal fired (e.g. `url_hint`) |
| `region_content_share` | float | content-signal share supporting the region |
| `source_dataset` | str | origin corpus: `fineweb` (English) or `fineweb2` (all other languages) |

## Usage

### Load the pointers for a locale

```python
import pyarrow.dataset as pad

d = pad.dataset("hf://datasets/Yusser/FineWeb-CLaR-region/data", partitioning="hive")
ptr = d.to_table(
    columns=["id", "dump", "url", "source_dataset"],
    filter=(pad.field("language_script") == "deu_Latn") & (pad.field("region") == "MD"),
)
```

### Get the source text from FineWeb / FineWeb-2

Rows carry no text; join it back from the origin corpus **by document id**. The
`source_dataset` column picks the corpus (`fineweb` for English locales,
`fineweb2` for everything else), `dump` narrows FineWeb to the right subset,
and `language_script` names the FineWeb-2 config:

```python
from datasets import load_dataset

ids = set(ptr.column("id").to_pylist())
source = ptr.column("source_dataset")[0].as_py()

if source == "fineweb":                      # English: one config per CC dump
    streams = [
        load_dataset("HuggingFaceFW/fineweb", name=dump, split="train", streaming=True)
        for dump in sorted(set(ptr.column("dump").to_pylist()))
    ]
else:                                        # FineWeb-2: one config per language
    streams = [load_dataset("HuggingFaceFW/fineweb-2", name="deu_Latn",
                            split="train", streaming=True)]

texts = {}
for stream in streams:
    for row in stream:
        if row["id"] in ids:
            texts[row["id"]] = row["text"]
            if len(texts) == len(ids):
                break
```

Streaming scans the whole config to find the matching ids — fine for small
locales, slow for large ones. For bulk extraction, `snapshot_download` the
origin parquet shards of the relevant dumps and filter by `id` (or restrict
FineWeb-2 by its `dump` column) with pyarrow instead of streaming.

## References

```bibtex
@inproceedings{penedo2024fineweb,
  title     = {The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale},
  author    = {Penedo, Guilherme and Kydl{\'i}{\v{c}}ek, Hynek and Ben Allal, Loubna and Lozhkov, Anton and Mitchell, Margaret and Raffel, Colin and Von Werra, Leandro and Wolf, Thomas},
  booktitle = {NeurIPS Datasets and Benchmarks},
  year      = {2024}
}

@article{penedo2025fineweb2,
  title   = {FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language},
  author  = {Penedo, Guilherme and Kydl{\'i}{\v{c}}ek, Hynek and Sabol{\v{c}}ec, Vinko and Messmer, Bettina and Foroutan, Negar and Jaggi, Martin and von Werra, Leandro and Wolf, Thomas},
  journal = {arXiv preprint arXiv:2506.20920},
  year    = {2025}
}
```

## Provenance & license

Document pointers and metadata derive from FineWeb / FineWeb-2 (ODC-By 1.0, subject to the [CommonCrawl ToU](https://commoncrawl.org/terms-of-use)) and are redistributed under the same ODC-By 1.0 terms. Region attribution is fully automatic (URL country-code hints and content-based signals) — no human labeling.