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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: legmlai/legml-v1.0-base |
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tags: |
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- llama-factory |
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- full |
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- generated_from_trainer |
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model-index: |
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- name: legml-v1.0-instruct |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: gpqa-fr |
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type: ai2_arc |
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config: le-leadboard/gpqa-fr |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc |
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value: 14.56 |
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name: accuracy |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: IFEval-fr |
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type: le-leadboard/IFEval-fr |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc |
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value: 13.55 |
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name: accuracy |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMMLU-fr |
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type: le-leadboard/MMMLU-fr |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 64.57 |
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name: accuracy |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: bbh-fr |
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type: le-leadboard/bbh-fr |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc |
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value: 38.71 |
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name: accuracy |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: musr-fr |
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type: le-leadboard/musr-fr |
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config: le-leadboard/musr-fr |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 4.41 |
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name: accuracy |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MATH_LVL5_fr |
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type: le-leadboard/MATH_LVL5_fr |
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config: le-leadboard/MATH_LVL5_fr |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 34.44 |
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name: accuracy |
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datasets: |
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- legmlai/finefrench-v1 |
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- legmlai/openhermes-fr |
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language: |
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- fr |
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--- |
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# legml-v1.0-instruct — L’Excellence Française de l’Instruction-Tuning |
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<div align="center"> |
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<img src="https://cdn-avatars.huggingface.co/v1/production/uploads/639c5c448a34ed9a404a956b/d0-xNWyRNOzlrCwOZD3Qf.png" alt="legml.ai" width="120"/> |
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**L’IA pure qui forme l’IA : un corpus 100 % francophone sélectionné et contrôlé** |
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**Curated by [legml.ai](https://legml.ai) – Leader in AI Data Curation & Quality Assurance** |
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</div> |
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--- |
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## 1 • Présentation |
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**`legmlai/legml-v1.0-instruct`** est la déclinaison *instruction-tuned* de **legml-v1.0-base** (Qwen-3 · 8 B). |
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Elle a été affinée sur **[Open-Hermes-FR](https://huggingface.co/datasets/legmlai/openhermes-fr)**, un corpus de **799 875** paires instruction/réponse exclusivement en français, issu de la traduction puis distillation d’OpenHermes original :contentReference[oaicite:0]{index=0}. |
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Projet conçu et maintenu par **[Mohamad Alhajar](https://www.linkedin.com/in/mohamad-alhajar/)**. |
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> **🙏 Merci à [Nebius](https://nebius.ai/)** pour le sponsoring GPU : **24 × H100 80 Go** qui ont permis cet entraînement. |
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--- |
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## 2 • Spécifications |
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| Paramètre | Valeur | |
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|-----------|--------| |
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| **Base** | `legmlai/legml-v1.0-base` (Qwen-3 · 8 B) | |
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| **Taille modèle** | ≈ 16 Go (fp16) / 8 Go (bf16) | |
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| **Jeu d’instructions** | Open-Hermes-FR – 799 875 paires, 100 % français :contentReference[oaicite:1]{index=1} | |
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| **Méthode** | SFT multi-tour + DPO léger | |
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| **Licence** | Apache-2.0 | |
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--- |
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## 3 • À propos d’Open-Hermes-FR |
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- **Origine** : traduction GPT-4o → français, puis génération des réponses et filtrage automatique. |
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- **Taille** : ~ 800 k exemples, schéma `prompt` / `accepted_completion` (+ flags qualité) :contentReference[oaicite:2]{index=2} |
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- **Licence** : ODC-BY 1.0 (libre, obligation d’attribution) :contentReference[oaicite:3]{index=3} |
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- **Objectif** : fournir un socle cohérent et riche pour l’alignement des LLMs francophones (dialogue, raisonnement, QA). |
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--- |
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## 4 • Exemple d’utilisation « chat » |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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import torch |
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device = "cuda" if torch.cuda.is_available() else "cpu" |
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model_id = "legmlai/legml-v1.0-instruct" |
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tok = AutoTokenizer.from_pretrained(model_id) |
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model = AutoModelForCausalLM.from_pretrained( |
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model_id, |
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device_map="auto", |
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torch_dtype="auto" |
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) |
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messages = [ |
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{"role": "system", |
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"content": "Tu es un assistant francophone rigoureux et bienveillant."}, |
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{"role": "user", |
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"content": "Explique-moi la relativité restreinte en trois points."} |
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] |
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prompt = tok.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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inputs = tok(prompt, return_tensors="pt").to(device) |
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out = model.generate( |
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**inputs, |
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temperature=0.4, |
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top_p=0.9, |
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max_new_tokens=512, |
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repetition_penalty=1.05 |
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) |
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print(tok.decode(out[0, inputs["input_ids"].shape[-1]:], skip_special_tokens=True)) |
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```` |
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--- |
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## 5 • Hyper-paramètres conseillés |
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| Scénario | Température | top-p | max\_new\_tokens | |
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| --------------------- | ----------- | ----- | ---------------- | |
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| Réponse factuelle | 0.3 – 0.5 | 0.9 | 128 – 256 | |
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| Explication détaillée | 0.4 – 0.6 | 0.9 | 512 – 768 | |
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| Création littéraire | 0.7 – 0.9 | 0.95 | ≥ 512 | |
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--- |
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## 6 • Limitations connues |
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1. **Connaissances post-avril 2025** limitées — vérifiez toujours les faits récents. |
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2. **Raisonnement mathématique compétition** encore perfectible. |
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3. **Biais** : certaines traces des datasets sources et de GPT-4o subsistent. |
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--- |
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## 7 • Citation |
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``` |
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@misc{legml2025_instruct, |
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title = {legml-v1.0-instruct : French Instruction-Tuned LLM}, |
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author = {Mohamad Alhajar}, |
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howpublished = {https://huggingface.co/legmlai/legml-v1.0-instruct}, |
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year = {2025} |
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} |
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``` |
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--- |
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© 2025 – [legml.ai](https://legml.ai) • Apache-2.0 |
