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Datasets:
Tree-AI-lab
/
kouman-code-sft-3.3m

Tasks:
Text Generation
Modalities:
Text
Formats:
json
Languages:
French
Baoulé
Dyula
Size:
1M - 10M
Tags:
kouman
code
sft
python
javascript
html
Libraries:
Datasets
Dask
License:
Dataset card Data Studio Files
xet
 Community
issoufzousko07 commited on
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feat: publication officielle corpus de programmation Kouman IA 3.375M (135 shards)

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  1. README.md +90 -0
  2. calculatrice__bci_bci__avance.jsonl.gz +3 -0
  3. calculatrice__bci_bci__debutant.jsonl.gz +3 -0
  4. calculatrice__bci_bci__intermediaire.jsonl.gz +3 -0
  5. calculatrice__bci_dyu__avance.jsonl.gz +3 -0
  6. calculatrice__bci_dyu__debutant.jsonl.gz +3 -0
  7. calculatrice__bci_dyu__intermediaire.jsonl.gz +3 -0
  8. calculatrice__bci_fr__avance.jsonl.gz +3 -0
  9. calculatrice__bci_fr__debutant.jsonl.gz +3 -0
  10. calculatrice__bci_fr__intermediaire.jsonl.gz +3 -0
  11. calculatrice__dyu_bci__avance.jsonl.gz +3 -0
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  20. calculatrice__fr_bci__avance.jsonl.gz +3 -0
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  23. calculatrice__fr_dyu__avance.jsonl.gz +3 -0
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  26. calculatrice__fr_fr__avance.jsonl.gz +3 -0
  27. calculatrice__fr_fr__debutant.jsonl.gz +3 -0
  28. calculatrice__fr_fr__intermediaire.jsonl.gz +3 -0
  29. interface_architecture__bci_bci__avance.jsonl.gz +3 -0
  30. interface_architecture__bci_bci__debutant.jsonl.gz +3 -0
  31. interface_architecture__bci_bci__intermediaire.jsonl.gz +3 -0
  32. interface_architecture__bci_dyu__avance.jsonl.gz +3 -0
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  35. interface_architecture__bci_fr__avance.jsonl.gz +3 -0
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  44. interface_architecture__dyu_fr__avance.jsonl.gz +3 -0
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  47. interface_architecture__fr_bci__avance.jsonl.gz +3 -0
  48. interface_architecture__fr_bci__debutant.jsonl.gz +3 -0
  49. interface_architecture__fr_bci__intermediaire.jsonl.gz +3 -0
  50. interface_architecture__fr_dyu__avance.jsonl.gz +3 -0
README.md ADDED
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+ ---
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+ language:
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+ - fr
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+ - bci
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+ - dyu
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+ license: cc-by-4.0
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+ task_categories:
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+ - text-generation
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+ tags:
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+ - kouman
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+ - code
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+ - sft
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+ - python
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+ - javascript
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+ - html
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+ - baoulé
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+ - dioula
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+ - french
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+ - west-africa
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+ - ivory-coast
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+ pretty_name: "Kouman IA — Corpus de Programmation SFT 3.375M"
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+ size_categories:
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+ - 1M<n<10M
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+ ---
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+
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+ # 🇨🇮 Kouman IA — Corpus de Programmation SFT (3 375 000 dialogues)
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+
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+ Corpus massif d'entraînement supervisé (**SFT**) orienté vers le code et l'ingénierie logicielle pour le modèle souverain africain **Kouman IA** développé par **Tree IA labs**.
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+
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+ ## 📊 Structure & Répartition
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+
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+ Le corpus est structuré en **135 shards** compressés en gzip (`.jsonl.gz`), totalisant **3 375 000 paires instruction/code** réparties de manière rigoureusement équilibrée : **exactement 25 000 exemples par cellule**.
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+
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+ | Dimension | Nombre | Exemples | Détails |
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+ |---|---:|---:|---|
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+ | **Familles applicatives** | 5 | 675 000 chacune | Sites web, calculatrices, scripts Python, jeux Python, applications avec architecture complète |
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+ | **Paires linguistiques** | 9 | 375 000 chacune | `fr_fr`, `dyu_dyu`, `bci_bci`, `dyu_fr`, `bci_fr`, `fr_dyu`, `fr_bci`, `dyu_bci`, `bci_dyu` |
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+ | **Niveaux de difficulté** | 3 | 1 125 000 chacun | Débutant, Intermédiaire, Avancé |
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+ | **Total cellules** | **135** | **25 000 chacune** | **3 375 000 dialogues au total** |
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+
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+ ## 🛠 Format des données
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+
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+ Chaque exemple est un objet JSON conforme à la structure conversationnelle Kouman IA :
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+
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+ ```json
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+ {
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+ "messages": [
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+ {"role": "user", "content": "..."},
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+ {"role": "assistant", "content": "```python\n...\n```"}
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+ ],
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+ "metadata": {
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+ "family": "script_python",
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+ "language_pair": "fr_bci",
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+ "difficulty": "intermediaire",
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+ "task_id": "...",
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+ "human_reviewed": false
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+ }
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+ }
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+ ```
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+
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+ ## 🔍 Validation & Contrôles Qualité
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+
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+ - **Scan intégral (3 375 000 lignes)** : 0 erreur de syntaxe JSON, aucun message vide, rôles `user`/`assistant` alternés sans rôle système.
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+ - **Syntaxe du code** : Validée sur 540 échantillons représentatifs via `ast.parse` (Python), `HTMLParser` (HTML) et Node.js (JavaScript).
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+ - **Unicité** : Unicité textuelle exacte vérifiée au sein de chaque cellule.
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+ - **Traductions locales (Baoulé & Dioula)** : Produites par traduction automatique, en attente de validation native par des locuteurs certifiés (`human_reviewed: false`).
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+
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+ ## 🚀 Utilisation avec Python & Datasets
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+
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+ ### Lecture directe en streaming (sans décompresser tout le corpus)
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+
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+ ```python
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+ import gzip, json, glob
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+
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+ def charger_dialogues(repertoire="."):
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+ for chemin in sorted(glob.glob(f"{repertoire}/*.jsonl.gz")):
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+ with gzip.open(chemin, "rt", encoding="utf-8") as f:
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+ for ligne in f:
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+ yield json.loads(ligne)
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+ ```
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+
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+ ## 📜 Empreintes & Traçabilité
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+
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+ - **SHA-256 `manifest.json`** : `38177ba9abe845998b3b9320bf621b9367ce1abc38151bacb09c412721a9e2b7`
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+ - **Volume total compressé** : 197 112 841 octets (~188 Mo sur 135 shards)
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+
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+ ## 🏛 Licence & Crédits
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+
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+ - **Concepteur & Développeur :** [Tree IA labs](https://huggingface.co/Tree-AI-lab)
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+ - **Licence :** CC BY 4.0
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