README.md

---
pretty_name: Lucie Training Dataset
license: cc-by-nc-sa-4.0
language:
- en
- fr
- de
- es
- it
- code
multilinguality:
- multilingual
task_categories:
- text-generation
- text2text-generation
task_ids:
- language-modeling
tags:
- text-generation
- conditional-text-generation
size_categories:
- n>1T
viewer: true
configs:
- config_name: default
  data_files:
  - path: data/*/*/*/*parquet
    split: train
- config_name: en
  data_files:
  - path: data/natural/en/*/*parquet
    split: train
- config_name: fr
  data_files:
  - path: data/natural/fr/*/*parquet
    split: train
- config_name: de
  data_files:
  - path: data/natural/de/*/*parquet
    split: train
- config_name: es
  data_files:
  - path: data/natural/es/*/*parquet
    split: train
- config_name: it
  data_files:
  - path: data/natural/it/*/*parquet
    split: train
- config_name: de,fr
  data_files:
  - path: data/natural/de-fr/*/*.parquet
    split: train
- config_name: es,en
  data_files:
  - path: data/natural/es-en/*/*.parquet
    split: train
- config_name: fr,en
  data_files:
  - path: data/natural/fr-en/*/*.parquet
    split: train
- config_name: it,en
  data_files:
  - path: data/natural/it-en/*/*.parquet
    split: train
- config_name: natural
  data_files:
  - path: data/natural/*/*/*.parquet
    split: train
- config_name: code
  data_files:
  - path: data/code/*/*/*parquet
    split: train
- config_name: code-assembly
  data_files:
  - path: data/code/assembly/*/*.parquet
    split: train
- config_name: code-c
  data_files:
  - path: data/code/c/*/*.parquet
    split: train
- config_name: code-c#
  data_files:
  - path: data/code/c#/*/*.parquet
    split: train
- config_name: code-c++
  data_files:
  - path: data/code/c++/*/*.parquet
    split: train
- config_name: code-clojure
  data_files:
  - path: data/code/clojure/*/*.parquet
    split: train
- config_name: code-dart
  data_files:
  - path: data/code/dart/*/*.parquet
    split: train
- config_name: code-elixir
  data_files:
  - path: data/code/elixir/*/*.parquet
    split: train
- config_name: code-erlang
  data_files:
  - path: data/code/erlang/*/*.parquet
    split: train
- config_name: code-fortran
  data_files:
  - path: data/code/fortran/*/*.parquet
    split: train
- config_name: code-go
  data_files:
  - path: data/code/go/*/*.parquet
    split: train
- config_name: code-haskell
  data_files:
  - path: data/code/haskell/*/*.parquet
    split: train
- config_name: code-java
  data_files:
  - path: data/code/java/*/*.parquet
    split: train
- config_name: code-javascript
  data_files:
  - path: data/code/javascript/*/*.parquet
    split: train
- config_name: code-julia
  data_files:
  - path: data/code/julia/*/*.parquet
    split: train
- config_name: code-kotlin
  data_files:
  - path: data/code/kotlin/*/*.parquet
    split: train
- config_name: code-lua
  data_files:
  - path: data/code/lua/*/*.parquet
    split: train
- config_name: code-mathematica
  data_files:
  - path: data/code/mathematica/*/*.parquet
    split: train
- config_name: code-matlab
  data_files:
  - path: data/code/matlab/*/*.parquet
    split: train
- config_name: code-ocaml
  data_files:
  - path: data/code/ocaml/*/*.parquet
    split: train
- config_name: code-perl
  data_files:
  - path: data/code/perl/*/*.parquet
    split: train
- config_name: code-php
  data_files:
  - path: data/code/php/*/*.parquet
    split: train
- config_name: code-python
  data_files:
  - path: data/code/python/*/*.parquet
    split: train
- config_name: code-r
  data_files:
  - path: data/code/r/*/*.parquet
    split: train
- config_name: code-racket
  data_files:
  - path: data/code/racket/*/*.parquet
    split: train
- config_name: code-ruby
  data_files:
  - path: data/code/ruby/*/*.parquet
    split: train
- config_name: code-rust
  data_files:
  - path: data/code/rust/*/*.parquet
    split: train
- config_name: code-scala
  data_files:
  - path: data/code/scala/*/*.parquet
    split: train
- config_name: code-swift
  data_files:
  - path: data/code/swift/*/*.parquet
    split: train
- config_name: code-tex
  data_files:
  - path: data/code/tex/*/*.parquet
    split: train
- config_name: code-typescript
  data_files:
  - path: data/code/typescript/*/*.parquet
    split: train
- config_name: AmendementsParlement
  data_files:
  - path: data/natural/*/AmendementsParlement/*.parquet
    split: train
- config_name: AmericanStories
  data_files:
  - path: data/natural/*/AmericanStories/*.parquet
    split: train
- config_name: Claire
  data_files:
  - path: data/natural/*/Claire/*.parquet
    split: train
- config_name: Claire-en
  data_files:
  - path: data/natural/en/Claire/*.parquet
    split: train
- config_name: Claire-fr
  data_files:
  - path: data/natural/fr/Claire/*.parquet
    split: train
- config_name: CroissantAligned
  data_files:
  - path: data/natural/*/CroissantAligned/*.parquet
    split: train
- config_name: DiscoursPublics
  data_files:
  - path: data/natural/*/DiscoursPublics/*.parquet
    split: train
- config_name: Europarl
  data_files:
  - path: data/natural/*/Europarl/*.parquet
    split: train
- config_name: Europarl-de
  data_files:
  - path: data/natural/de/Europarl/*.parquet
    split: train
- config_name: Europarl-en
  data_files:
  - path: data/natural/en/Europarl/*.parquet
    split: train
- config_name: Europarl-es
  data_files:
  - path: data/natural/es/Europarl/*.parquet
    split: train
- config_name: Europarl-fr
  data_files:
  - path: data/natural/fr/Europarl/*.parquet
    split: train
- config_name: EuroparlAligned
  data_files:
  - path: data/natural/*/EuroparlAligned/*.parquet
    split: train
- config_name: EuroparlAligned-de,fr
  data_files:
  - path: data/natural/de-fr/EuroparlAligned/*.parquet
    split: train
- config_name: EuroparlAligned-es,en
  data_files:
  - path: data/natural/es-en/EuroparlAligned/*.parquet
    split: train
- config_name: EuroparlAligned-fr,en
  data_files:
  - path: data/natural/fr-en/EuroparlAligned/*.parquet
    split: train
- config_name: EuroparlAligned-it,en
  data_files:
  - path: data/natural/it-en/EuroparlAligned/*.parquet
    split: train
- config_name: Eurovoc
  data_files:
  - path: data/natural/*/Eurovoc/*.parquet
    split: train
- config_name: Eurovoc-de
  data_files:
  - path: data/natural/de/Eurovoc/*.parquet
    split: train
- config_name: Eurovoc-en
  data_files:
  - path: data/natural/en/Eurovoc/*.parquet
    split: train
- config_name: Eurovoc-es
  data_files:
  - path: data/natural/es/Eurovoc/*.parquet
    split: train
- config_name: Eurovoc-it
  data_files:
  - path: data/natural/it/Eurovoc/*.parquet
    split: train
- config_name: FineWebEdu
  data_files:
  - path: data/natural/*/FineWebEdu/*.parquet
    split: train
- config_name: GallicaMonographies
  data_files:
  - path: data/natural/*/GallicaMonographies/*.parquet
    split: train
- config_name: GallicaPress
  data_files:
  - path: data/natural/*/GallicaPress/*.parquet
    split: train
- config_name: Gutenberg
  data_files:
  - path: data/natural/*/Gutenberg/*.parquet
    split: train
- config_name: Gutenberg-de
  data_files:
  - path: data/natural/de/Gutenberg/*.parquet
    split: train
- config_name: Gutenberg-en
  data_files:
  - path: data/natural/en/Gutenberg/*.parquet
    split: train
- config_name: Gutenberg-es
  data_files:
  - path: data/natural/es/Gutenberg/*.parquet
    split: train
- config_name: Gutenberg-fr
  data_files:
  - path: data/natural/fr/Gutenberg/*.parquet
    split: train
- config_name: Gutenberg-it
  data_files:
  - path: data/natural/it/Gutenberg/*.parquet
    split: train
- config_name: HAL
  data_files:
  - path: data/natural/*/HAL/*.parquet
    split: train
- config_name: MathPile
  data_files:
  - path: data/natural/*/MathPile/*.parquet
    split: train
- config_name: OpenData
  data_files:
  - path: data/natural/*/OpenData/*.parquet
    split: train
- config_name: OpenEdition
  data_files:
  - path: data/natural/*/OpenEdition/*.parquet
    split: train
- config_name: PeS2o
  data_files:
  - path: data/natural/*/PeS2o/*.parquet
    split: train
- config_name: Persee
  data_files:
  - path: data/natural/*/Persee/*.parquet
    split: train
- config_name: RedPajama
  data_files:
  - path: data/natural/*/RedPajama/*.parquet
    split: train
- config_name: RedPajama-de
  data_files:
  - path: data/natural/de/RedPajama/*.parquet
    split: train
- config_name: RedPajama-es
  data_files:
  - path: data/natural/es/RedPajama/*.parquet
    split: train
- config_name: RedPajama-fr
  data_files:
  - path: data/natural/fr/RedPajama/*.parquet
    split: train
- config_name: RedPajama-it
  data_files:
  - path: data/natural/it/RedPajama/*.parquet
    split: train
- config_name: Stac
  data_files:
  - path: data/natural/*/Stac/*.parquet
    split: train
- config_name: TheStack
  data_files:
  - path: data/code/*/TheStack/*.parquet
    split: train
- config_name: Theses
  data_files:
  - path: data/natural/*/Theses/*.parquet
    split: train
- config_name: Wikipedia
  data_files:
  - path: data/natural/*/Wikipedia/*.parquet
    split: train
- config_name: Wikipedia-de
  data_files:
  - path: data/natural/de/Wikipedia/*.parquet
    split: train
- config_name: Wikipedia-en
  data_files:
  - path: data/natural/en/Wikipedia/*.parquet
    split: train
- config_name: Wikipedia-es
  data_files:
  - path: data/natural/es/Wikipedia/*.parquet
    split: train
- config_name: Wikipedia-fr
  data_files:
  - path: data/natural/fr/Wikipedia/*.parquet
    split: train
- config_name: Wikipedia-it
  data_files:
  - path: data/natural/it/Wikipedia/*.parquet
    split: train
- config_name: Wikisource
  data_files:
  - path: data/natural/*/Wikisource/*.parquet
    split: train
- config_name: Wiktionary
  data_files:
  - path: data/natural/*/Wiktionary/*.parquet
    split: train
- config_name: YouTube
  data_files:
  - path: data/natural/*/YouTube/*.parquet
    split: train
---

# Dataset Card

The Lucie Training Dataset is a curated collection of text data
in English, French, German, Spanish and Italian,
from the web,
video subtitles,
collections of books, newspapers, monographies, and magazines processed by Optical Character Recognition (OCR),
as well as collections of files in diverse programming languages.

It was used to pretrain [Lucie-7B](https://huggingface.co/OpenLLM-France/Lucie-7B),
a foundation LLM with strong capabilities in French and English.

## Dataset Description

This dataset was made to provide an extensive and diverse dataset for training Large Language Models (LLM),
with the following motivations in mind:
* Data mix:
    * French is as well represented as English
    (Lucie Training Dataset is one of the biggest of collection of French text data with a minimum of quality),
    to avoid that the LLM is culturally biased towards English.
    * German, Spanish and Italian are also represented to some extend,
    * Code is also included to boost the reasoning capabilities of LLM.
* Data filtering and deduplication:
    * The dataset is cleaned low-quality data
    * The dataset is cleaned from duplicates to some extend, following best practices.
* Ethics:
    * A special care was taken to respect copyright laws and the privacy of individuals.
      All books, newspapers, monographies, and magazines are in the public domain
  (which depends on the author's death date, and the country of publication).
    * There is no data from the web for which robots.txt files forbid crawling.

### Dataset Structure

The corpus contains the following information for each text sample:
* `text`: the text sample itself.
* `source`: an identifier for the source(s) of the text sample (`Wikipedia`, `RedPajama`, `Gutenberg`, …).
  The list of all sources is described in this document.
* `id`: an identifier that is unique among the source.
* `language`: the language of the text sample, which can be:
    * the ISO 639-1 code of a natural language: `en`, `fr`, `de`, `es`, or `it`;
    * the common name prefixed by "`code:`" of a programming language:  `code:python`, `code:c++`, …; or
    * a list of ISO 639-1 codes separated by commas, if the text sample is multilingual: `fr,en`, `de,fr`, `es,en`, `it,en`
     (or in the opposite order if the languages appear in the opposite order in the text).
* `url` (optional): the URL of the original text sample on the web, if available.
* `title` (optional): the title of the original text sample, if available.
* `author` (optional): the author of the original text sample, if available.
   Usually the author name in plain text, except for `Gutenberg` where it is the JSON serialized object of the author metadata.
* `date` (optional): the publication date of the original text sample, if available. The text format of the source depends on the source.
* `quality_signals` (optional): a list of quality signals about the text sample (that could be used for further filtering or sample weighting).
  It can include indicators computed by `fasttext` and `CCNet`, statistics about occurrences of characters, words, special characters, etc.
  This field is always a JSON serialized object.
* `extra` (optional): JSON serialized extra information about the text sample.
  This can include metadata about the source subset, the rights, etc.

Examples of metadata (except from `text`) are shown for each source in [metadata_examples.json](metadata_examples.json).

### Example use in python

Load the dataset using the `datasets` library:
```python
from datasets import load_dataset

kwargs = {"split": "train", "streaming": True}

dataset = load_dataset("OpenLLM-France/Lucie-Training-Dataset", **kwargs)
```

Several configurations are available to select a language, a source, or both, illustrated in the following examples.

Load data in French:
```python
dataset = load_dataset("OpenLLM-France/Lucie-Training-Dataset", "fr", **kwargs)
```
Load data where French and English are aligned:
```python
dataset = load_dataset("OpenLLM-France/Lucie-Training-Dataset", "fr,en", **kwargs)
```
Load data corresponding to files with programming languages:
```python
dataset = load_dataset("OpenLLM-France/Lucie-Training-Dataset", "code", **kwargs)
```
Load data in Python:
```python
dataset = load_dataset("OpenLLM-France/Lucie-Training-Dataset", "code:python", **kwargs)
```
Load data from Wikipedia (in available languages):
```python
dataset = load_dataset("OpenLLM-France/Lucie-Training-Dataset", "Wikipedia", **kwargs)
```
Load data from French pages of Wikipedia ([wikipedia.fr](https://www.wikipedia.fr/)):
```python
dataset = load_dataset("OpenLLM-France/Lucie-Training-Dataset", "Wikipedia-fr", **kwargs)
```