README.md

metadata

dataset_info:
  features:
    - name: ref
      dtype: string
    - name: title_main
      dtype: string
    - name: texte
      dtype: string
    - name: dateDebut
      dtype: int64
    - name: dateFin
      dtype: int64
    - name: num
      dtype: string
    - name: id
      dtype: string
    - name: cid
      dtype: string
    - name: type
      dtype: string
    - name: etat
      dtype: string
    - name: nota
      dtype: string
    - name: version_article
      dtype: string
    - name: ordre
      dtype: int64
    - name: conditionDiffere
      dtype: 'null'
    - name: infosComplementaires
      dtype: 'null'
    - name: surtitre
      dtype: 'null'
    - name: nature
      dtype: string
    - name: texteHtml
      dtype: string
    - name: dateFinExtension
      dtype: int64
    - name: versionPrecedente
      dtype: string
    - name: refInjection
      dtype: string
    - name: idTexte
      dtype: 'null'
    - name: idTechInjection
      dtype: string
    - name: origine
      dtype: string
    - name: dateDebutExtension
      dtype: int64
    - name: idEliAlias
      dtype: 'null'
    - name: cidTexte
      dtype: 'null'
    - name: sectionParentId
      dtype: string
    - name: multipleVersions
      dtype: bool
    - name: comporteLiensSP
      dtype: bool
    - name: sectionParentTitre
      dtype: string
    - name: infosRestructurationBranche
      dtype: 'null'
    - name: idEli
      dtype: 'null'
    - name: sectionParentCid
      dtype: string
    - name: numeroBo
      dtype: 'null'
    - name: infosRestructurationBrancheHtml
      dtype: 'null'
    - name: historique
      dtype: 'null'
    - name: infosComplementairesHtml
      dtype: 'null'
    - name: renvoi
      dtype: 'null'
    - name: fullSectionsTitre
      dtype: string
    - name: notaHtml
      dtype: string
    - name: inap
      dtype: 'null'
  splits:
    - name: train
      num_bytes: 432536720
      num_examples: 153983
  download_size: 185292857
  dataset_size: 432536720
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: apache-2.0
task_categories:
  - text-generation
language:
  - fr
tags:
  - legal
  - law
  - droit
  - fiscalité
pretty_name: Romulus, continued pre-trained models for French law

Romulus, continually pre-trained models for French law.

Romulus is a series of continually pre-trained models enriched in French law and intended to serve as the basis for a fine-tuning process on labeled data. Please note that these models have not been aligned for the production of usable text as they stand, and will certainly need to be fine-tuned for the desired tasks in order to produce satisfactory results.

The training corpus is made up of around 34,864,949 tokens (calculated with the meta-llama/Meta-Llama-3.1-8B tokenizer).

Citing & Authors

If you use this code in your research, please use the following BibTeX entry.

@misc{louisbrulenaudet2024,
  author =       {Louis Brulé Naudet},
  title =        {Romulus, continually pre-trained models for French law},
  year =         {2024}
  howpublished = {\url{https://huggingface.co/datasets/louisbrulenaudet/Romulus-cpt-fr}},
}

Feedback

If you have any feedback, please reach out at louisbrulenaudet@icloud.com.