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--- |
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license: cc |
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task_categories: |
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- text-generation |
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task_ids: |
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- language-modeling |
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pretty_name: ©️ Common Crawl Creative Commons |
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language: |
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- afr |
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- deu |
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- eng |
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- fra |
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- fry |
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- ita |
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- nld |
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- spa |
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configs: |
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- config_name: CC-MAIN-2024-51 |
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data_files: data/CC-MAIN-2024-51/**/*.parquet |
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- config_name: CC-MAIN-2024-51-af |
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data_files: |
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- split: train |
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path: data/CC-MAIN-2024-51/af/train-* |
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- config_name: CC-MAIN-2024-51-de |
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data_files: data/CC-MAIN-2024-51/de/*.parquet |
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- config_name: CC-MAIN-2024-51-en |
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data_files: data/CC-MAIN-2024-51/en/*.parquet |
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- config_name: CC-MAIN-2024-51-es |
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data_files: data/CC-MAIN-2024-51/es/*.parquet |
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- config_name: CC-MAIN-2024-51-fr |
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data_files: data/CC-MAIN-2024-51/fr/*.parquet |
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- config_name: CC-MAIN-2024-51-fy |
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data_files: data/CC-MAIN-2024-51/fy/*.parquet |
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- config_name: CC-MAIN-2024-51-it |
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data_files: data/CC-MAIN-2024-51/it/*.parquet |
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- config_name: CC-MAIN-2024-51-nl |
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data_files: data/CC-MAIN-2024-51/nl/*.parquet |
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- config_name: af |
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data_files: data/**/af/*.parquet |
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- config_name: de |
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data_files: data/**/de/*.parquet |
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- config_name: default |
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data_files: data/**/*.parquet |
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- config_name: en |
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data_files: data/**/en/*.parquet |
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- config_name: es |
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data_files: data/**/es/*.parquet |
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- config_name: fr |
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data_files: data/**/fr/*.parquet |
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- config_name: fy |
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data_files: data/**/fy/*.parquet |
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- config_name: it |
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data_files: data/**/it/*.parquet |
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- config_name: nl |
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data_files: data/**/nl/*.parquet |
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dataset_info: |
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config_name: CC-MAIN-2024-51-af |
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features: |
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- name: text |
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dtype: string |
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- name: id |
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dtype: string |
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- name: dump |
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dtype: string |
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- name: url |
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dtype: string |
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- name: date |
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dtype: string |
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- name: file_path |
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dtype: string |
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- name: license_abbr |
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dtype: string |
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- name: license_version |
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dtype: string |
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- name: license_location |
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dtype: string |
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- name: license_in_head |
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dtype: bool |
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- name: license_in_footer |
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dtype: bool |
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- name: potential_licenses |
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struct: |
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- name: abbr |
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sequence: string |
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- name: in_footer |
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sequence: bool |
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- name: in_head |
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sequence: bool |
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- name: location |
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sequence: string |
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- name: version |
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sequence: string |
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- name: license_parse_error |
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dtype: bool |
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- name: license_disagreement |
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dtype: bool |
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- name: language |
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dtype: string |
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- name: language_score |
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dtype: float64 |
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- name: in_fw2 |
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dtype: bool |
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splits: |
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- name: train |
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num_bytes: 75356511 |
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num_examples: 17733 |
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download_size: 41860751 |
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dataset_size: 75356511 |
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--- |
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> **Raw CommonCrawl crawls, annotated with potential Creative Commons license information** |
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**The licensing information is extracted from the web pages based on whether they link to Creative Commons licenses but false positives may occur!** While further filtering based on the location type of the license should improve the precision (e.g. by removing hyperlink (a_tag) references), false positives may still occur. |
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## Usage |
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```python |
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from datasets import load_dataset |
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# Everything |
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ds = load_dataset("BramVanroy/CommonCrawl-CreativeCommons") |
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# Single dump, all languages |
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ds = load_dataset("BramVanroy/CommonCrawl-CreativeCommons", "CC-MAIN-2024-51") |
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# Single language, all dumps |
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ds = load_dataset("BramVanroy/CommonCrawl-CreativeCommons", "nl") |
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# Single language, single dump |
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ds = load_dataset("BramVanroy/CommonCrawl-CreativeCommons", "CC-MAIN-2024-51-nl") |
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``` |
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## Fields |
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In some cases, multiple licenses are found on a single page. All licenses are collected in `potential_licenses`. From these, the "best guess" is selected |
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based on three criteria: |
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1. location_preference_order: meta_tag, json-ld, link_tag, a_tag |
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2. head_preference_order: True, False |
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3. footer_preference_order: True, False |
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Based on these criteria, the "best guessed" license is picked as the one in the `license_*` columns. Potential disagreement between multiple licenses is given in `license_disagreement`. |
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- text: the extracted text (unmodified) |
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- id: WARC-Record-ID |
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- dump: Common Crawl crawl |
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- url: original url for document |
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- date: crawl date |
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- file_path: file path on the S3 bucket |
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- license_abbr: the license type. Possible values: "cc-unknown" (recommended to filter this one out), "by", "by-sa", "by-nd", "by-nc", "by-nc-sa", "by-nc-nd", "zero", "certification", "mark". If multiple licenses were found (`potential_licenses`) |
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- license_version: the license version, e.g. "4.0" |
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- license_location: the location where the license was found. Possible values: "meta_tag", "json-ld", "link_tag", "a_tag" |
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- license_in_head: whether the license was found inside a `head` HTML element |
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- license_in_footer: whether the license was found inside a `footer` HTML element, or an HTML element that had `footer` in the ID or class name |
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- potential_licenses: |
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- abbr: list of all found license abbreviations |
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- version: list of all found license versions |
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- location: list of all found license locations |
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- in_head: list of whether licenses were found in the head |
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- in_footer: list of whether licenses were found in a footer |
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- license_parse_error: whether there was a problem when trying to extract the license, e.g. an unparseable HTML document |
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- license_disagreement: whether the `potential_licenses["abbr"]` disagree, i.e., different types of licenses were found. License *versions* are not included in the comparison! |
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- language: the language, as detected by fastText `ft176` |
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- language_score: the language identification confidence score |
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- found_in_fw2: whether this sample was found in FineWeb-2. Crawls that are more recent than FW2 (everything after 2024-18) is marked as None |
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## Progress |
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The attempt is to at least process all five RedPyjama crawls + `CC-MAIN-2024-51`. |
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Done: |
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- CC-MAIN-2024-51 |
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Running: |
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- CC-MAIN-2019-30 |
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To do: |
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- CC-MAIN-2019-30 |
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- CC-MAIN-2020-05 |
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- CC-MAIN-2021-04 |
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- CC-MAIN-2022-05 |
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- CC-MAIN-2023-06 |
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- CC-MAIN-2024-51 |
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## Languages |
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The following languages are included. |
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- afr_Latn |
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- deu_Latn |
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- eng_Latn |
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- fra_Latn |
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- fry_Latn |
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- ita_Latn |
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- nld_Latn |
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- spa_Latn |
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## Recommendations |
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- Raw CommonCrawl data is processed in an attempt to extract licensing information. No quality filtering is done!! It is **highly** recommended to filter this data further on quality, fluency, toxicity, etc. |
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- Similarly, the data has **not been deduplicated**. |
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- The licenses include all possible Creative Commons licenses, including non-commercial ones. Take care about what kind of data you wish to use, and filter out non-commercial licenses when needed. |
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- The column `license_disagreement` indicates whether multiple licenses were found that have not the same abbreviation, e.g. `cc-by` and `cc-by-nc`. It is recommended to filter these out. |
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- The column `license_parse_error` indicates whether an error occurred when parsing the license. You probably want to filter out documents where this was the case, though this should be extremely rare. |
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- Unsurpisingly, the data contains a lot of Wikipedia/Wikimedia content. Depending on what you need, you may wish to filter those out. For Wikipedia specifically, you may opt to use the more thoroughly parsed (but potentially more outdated) [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) set. |
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- In exceptional cases, a link to creativecommons.org is found but the exact license could not be found. These are under `license_abbr="cc-unknown"` which you may wish to filter out. |
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## Acknowledgments |
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- [TNO](https://www.tno.nl/nl/), who funded the work hours to accomplish this collection. They intend to use parts of this material for the [GPT-NL project](https://gpt-nl.nl/). |
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- [Flemish Supercomputer Center](https://www.vscentrum.be/) for part of the compute under grant 2024-107 |
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- Guilherme Penedo ([@guipenedo](https://huggingface.co/guipenedo)) and the rest of the [FineWeb](https://huggingface.co/datasets/HuggingFaceFW/fineweb) and [datatrove](https://github.com/huggingface/datatrove) team for the help and insights |
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- ML6 and specifically Robin Van Craenenbroek for their [Fondant Creative Commons](https://github.com/ml6team/fondant-usecase-filter-creative-commons/tree/add-fondant-usecase-cc-image-extraction) filter for image datasets. While my approach is different, their code did serve as inspiration. |
