# facebookresearch/cc_net

Tools to download and cleanup Common Crawl data

Repository: https://github.com/facebookresearch/cc_net
Canonical: https://ross.abutalabs.com/products/cc_net
Language: Python
License: MIT
License Family: permissive
Archived: true
Last push: 2023-04-25T08:02:37+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2500, "days_push": 1226, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1045, forks 154 (observed 2026-08-28T04:03:21.532845+00:00)

## What it is
CCNet is a Python pipeline from Facebook AI Research for downloading, deduplicating, and cleaning Common Crawl web data into high-quality monolingual datasets. It uses language models and perplexity filtering to extract per-language corpora for training multilingual language models.

## Use cases
- download and clean Common Crawl snapshots
- extract monolingual corpora from web crawl data
- filter web text by language and perplexity
- deduplicate paragraphs across crawl data
- reproduce the CCNet corpus for multilingual model training
- prepare pretraining data for XLM-R style models

## When to choose
- you need large-scale multilingual training corpora from Common Crawl
- you want to reproduce the CCNet or XLM-R data pipeline
- you need language identification and LM-based quality filtering on crawl data

## When to avoid
- you only need a small curated dataset rather than web-scale crawling
- you need a maintained tool with recent updates and broad platform support
- you cannot run heavy CPU pipelines or external tools like KenLM and SentencePiece

## Facets
- artifact type: library
- maturity: maintenance
- function: etl, nlp, data-science, web-scraping, parser
- domain: machine-learning, big-data
- platform: python, cli
- tags: common-crawl, corpus-mining, language-model-filtering, dataset-preparation, deduplication, natural-language-processing, data-engineering, linux

## Member repositories
- facebookresearch/cc_net (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:21.532845+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:02:04.651372+00:00, confidence not recorded.
  - readme: https://github.com/facebookresearch/cc_net (fetched 2026-08-28T04:03:21.532845+00:00, sha e1eb6f30102a)
  - registry_pypi: https://pypi.org/pypi/cc_net/json (fetched 2026-08-29T13:03:13.831525+00:00, sha d7e243630cb3)
- Data as of 2026-08-30T08:39:29.467469+00:00.