> For the complete documentation index, see [llms.txt](https://unsloth.ai/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://unsloth.ai/docs/fr/commencer/unsloth-notebooks.md).

# Notebooks Unsloth

Entraînez votre propre modèle avec nos notebooks, alimentés par du calcul GPU gratuit. Cliquez sur Exécuter tout (ou enregistrez localement), ajoutez votre jeu de données, entraînez, puis déployez. Vous pouvez utiliser n'importe quel modèle dans les notebooks.

<a href="/pages/2bdfa5349e5d636154595876b11e5db5e1f9e9d6#grpo-reasoning-rl" class="button secondary">GRPO (RL)</a><a href="/pages/2bdfa5349e5d636154595876b11e5db5e1f9e9d6#text-to-speech-tts" class="button secondary">Synthèse vocale</a><a href="/pages/2bdfa5349e5d636154595876b11e5db5e1f9e9d6#vision-multimodal" class="button secondary">Vision</a><a href="/pages/2bdfa5349e5d636154595876b11e5db5e1f9e9d6#embedding-models" class="button secondary">Embedding</a><a href="/pages/2bdfa5349e5d636154595876b11e5db5e1f9e9d6#kaggle-notebooks" class="button secondary">Kaggle</a>

Consultez aussi notre dépôt GitHub pour nos notebooks : [github.com/unslothai/notebooks](https://github.com/unslothai/notebooks/)

## Notebooks Colab

**Présentation de notre** [**Unsloth Studio**](/docs/fr/nouveau/studio.md)✨ **notebook.** Entraînez et exécutez des modèles de moins de 22B paramètres :

{% embed url="<https://colab.research.google.com/github/unslothai/unsloth/blob/main/studio/Unsloth_Studio_Colab.ipynb>" %}

### Notebooks SFT standards :

* [**Muse Glimmer (30B)**](/docs/fr/modeles/muse-glimmer/train.md) **•** [Conversationnel (Kaggle)](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/notebooks/blob/main/nb/Kaggle-Muse_Glimmer_\(30B\)-Conversational.ipynb\&accelerator=nvidiaTeslaT4)  • [Vision (Kaggle)](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/notebooks/blob/main/nb/Kaggle-Muse_Glimmer_\(30B\)-Vision.ipynb\&accelerator=nvidiaTeslaT4)
* [**Gemma 4**](/docs/fr/modeles/gemma-4/train.md)**:** [E4B **(Vision)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(E4B\)-Vision.ipynb) **•** [E2B **(Texte)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(E2B\)-Text.ipynb) **•** [E2B **(Audio)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(E2B\)-Audio.ipynb) **•** [**31B** (Kaggle)](https://www.kaggle.com/code/danielhanchen/gemma4-31b-unsloth) **•** [**Inférence**](https://colab.research.google.com/github/unslothai/unsloth/blob/main/studio/Unsloth_Studio_Colab.ipynb)
* [**Qwen3.5**](/docs/fr/modeles/qwen3.5/fine-tune.md)**:** [**0.8B**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_5_\(0_8B\)_Vision.ipynb) • [**2B**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_5_\(2B\)_Vision.ipynb) • [**4B**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_5_\(4B\)_Vision.ipynb)
* [gpt-oss (20b)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-Fine-tuning.ipynb) • [Inférence](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/GPT_OSS_MXFP4_\(20B\)-Inference.ipynb) • [Affinage](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-Fine-tuning.ipynb)
* [EmbeddingGemma (300M)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/EmbeddingGemma_\(300M\).ipynb)
* [Qwen3 (14B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(14B\)-Reasoning-Conversational.ipynb) • [**Qwen3-VL (8B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL_\(8B\)-Vision.ipynb)
* [**Qwen3-2507-4B**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)-Instruct.ipynb) • [Réflexion](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)-Thinking.ipynb) • [Instruct](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)-Instruct.ipynb)
* [Gemma 3 (4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\).ipynb) • [Texte](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\).ipynb) • [Vision](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\)-Vision.ipynb) • [270M](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(270M\).ipynb) • [**FunctionGemma**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\).ipynb)
* [Gemma 3n (E4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_\(4B\)-Conversational.ipynb) • [Texte](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_\(4B\)-Conversational.ipynb) • [Vision](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_\(4B\)-Vision.ipynb) • [Audio](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_\(4B\)-Audio.ipynb)
* [**Mistral Ministral 3**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Ministral_3_VL_\(3B\)_Vision.ipynb)
* [**DeepSeek-OCR 2**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Deepseek_OCR_2_\(3B\).ipynb)&#x20;
* [IBM Granite-4.0-H](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Granite4.0.ipynb)
* [Phi-4 (14B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_4-Conversational.ipynb)
* [Llama 3.1 (8B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_\(8B\)-Alpaca.ipynb) • [Llama 3.2 (1B + 3B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(1B_and_3B\)-Conversational.ipynb)

### GRPO (RL de raisonnement) :

* [**Muse Glimmer (30B)**](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/notebooks/blob/main/nb/Kaggle-Muse_Glimmer_\(30B\)-GRPO.ipynb\&accelerator=nvidiaTeslaT4)
* [**Gemma 4 E2B**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(E2B\)_Reinforcement_Learning_Sudoku_Game.ipynb) - nouveau
* [**Qwen3.5 (4B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_5_\(4B\)_Vision_GRPO.ipynb) - GRPO Vision
* [gpt-oss-20b](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) (création automatique des kernels)
* [Mistral Ministral 3](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Ministral_3_\(3B\)_Reinforcement_Learning_Sudoku_Game.ipynb) (résolution du sudoku) - nouveau
* [Qwen3-8B - **FP8**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_8B_FP8_GRPO.ipynb) (L4) - nouveau
* [Llama-3.2-1B - **FP8**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama_FP8_GRPO.ipynb) (L4) - nouveau
* [gpt-oss-20b](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt_oss_\(20B\)_Reinforcement_Learning_2048_Game.ipynb) (victoire automatique au jeu 2048)&#x20;
* [Qwen3-VL (8B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL_\(8B\)-Vision-GRPO.ipynb) - GSPO Vision
* [Qwen3 (4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)-GRPO.ipynb) - LoRA GRPO avancée
* [Gemma 3 (4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\)-Vision-GRPO.ipynb) - GSPO Vision
* [gpt-oss-20b](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/OpenEnv_gpt_oss_\(20B\)_Reinforcement_Learning_2048_Game.ipynb) (exemple OpenEnv 2048)
* [DeepSeek-R1-0528-Qwen3 (8B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/DeepSeek_R1_0528_Qwen3_\(8B\)_GRPO.ipynb) (pour un cas d'usage multilingue)
* [Gemma 3 (1B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(1B\)-GRPO.ipynb)
* [Llama 3.2 (3B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Advanced_Llama3_2_\(3B\)_GRPO_LoRA.ipynb) - LoRA GRPO avancée
* [Llama 3.1 (8B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_\(8B\)-GRPO.ipynb)
* [Phi-4 (14B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_4_\(14B\)-GRPO.ipynb)
* [Mistral v0.3 (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-GRPO.ipynb)
* [Environnement multi-agents NeMo Gym ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/NeMo-Gym-Multi-Environment.ipynb)(Plusieurs environnements agentiques)

### Synthèse vocale (TTS) :

* [Sesame-CSM (1B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Sesame_CSM_\(1B\)-TTS.ipynb)
* [Orpheus-TTS (3B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Orpheus_\(3B\)-TTS.ipynb)
* [Whisper Large V3](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Whisper.ipynb) - Reconnaissance vocale (STT)
* [Llasa-TTS (1B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llasa_TTS_\(1B\).ipynb)
* [Spark-TTS (0.5B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Spark_TTS_\(0_5B\).ipynb)
* [Oute-TTS (1B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Oute_TTS_\(1B\).ipynb)

**Reconnaissance vocale (SST) :**

* [**Gemma 4 (E2B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(E2B\)-Audio.ipynb) **- Audio - nouveau**
* [Whisper-Large-V3](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Whisper.ipynb)
* [Gemma 3n (E4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_\(4B\)-Audio.ipynb) - Audio

### Vision (multimodale) :

* [**Gemma 4**](/docs/fr/modeles/gemma-4/train.md)**:** [E2B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(E2B\)-Vision.ipynb) **•** [**31B** (Kaggle)](https://www.kaggle.com/code/danielhanchen/gemma4-31b-unsloth) - nouveau
* [**Qwen3.5**](/docs/fr/modeles/qwen3.5/fine-tune.md)**:** [**0.8B**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_5_\(0_8B\)_Vision.ipynb) • [**2B**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_5_\(2B\)_Vision.ipynb) • [**4B**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_5_\(4B\)_Vision.ipynb) - nouveau
* [**Qwen3-VL (8B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL_\(8B\)-Vision.ipynb)
* [**Mistral Ministral 3**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Ministral_3_VL_\(3B\)_Vision.ipynb)
* [**DeepSeek-OCR**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Deepseek_OCR_\(3B\).ipynb)
* [**Paddle-OCR (1B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Paddle_OCR_\(1B\)_Vision.ipynb)
* [Gemma 3n (E4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_\(4B\)-Vision.ipynb)
* [Gemma 3 (4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\)-Vision.ipynb)
* [Llama 3.2 Vision (11B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(11B\)-Vision.ipynb)
* [Qwen2.5-VL (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_VL_\(7B\)-Vision.ipynb)
* [Pixtral (12B) 2409](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Pixtral_\(12B\)-Vision.ipynb)
* [Qwen3-VL](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL_\(8B\)-Vision-GRPO.ipynb) - GSPO Vision - nouveau
* [Qwen2.5-VL](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2_5_7B_VL_GRPO.ipynb) - GSPO Vision
* [Gemma 3 (4B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\)-Vision-GRPO.ipynb) - GSPO Vision

### Modèles d'embedding :

* [EmbeddingGemma (300M)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/EmbeddingGemma_\(300M\).ipynb) - nouveau
* [Qwen3-Embedding 4B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_Embedding_\(4B\).ipynb) - nouveau
* [Qwen3-Embedding 0.6B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_Embedding_\(0_6B\).ipynb) - nouveau
* [BGE M3](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/BGE_M3.ipynb) - nouveau
* [ModernBERT-large](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/bert_classification.ipynb) - nouveau
* [All-MiniLM-L6-v2](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/All_MiniLM_L6_v2.ipynb) - nouveau
* [GTE ModernBert](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/ModernBert.ipynb) - nouveau

### Grands LLM :

**Notebooks pour grands modèles :** Ils dépassent l'offre gratuite de 15 Go de VRAM de Colab. Avec les nouveaux GPU 80 Go de Colab, vous pouvez affiner des modèles de 120B paramètres.

{% hint style="info" %}
Un abonnement ou des crédits Colab sont requis. Nous **n'** ne gagnons rien avec ces notebooks.
{% endhint %}

* [**Gemma-4-31B**](https://www.kaggle.com/code/danielhanchen/gemma4-31b-unsloth) - nouveau et **GRATUIT**
* [**DiffusionGemma**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/DiffusionGemma_\(26B-A4B\)-Sudoku.ipynb) - nouveau
* [Gemma-4-26B-A4B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(26B_A4B\)-Vision.ipynb) - nouveau
* [Gemma-4-31B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(31B\)-Vision.ipynb) - nouveau
* [Qwen3.5-35B-A3B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_5_MoE.ipynb)
* [Qwen3.5‑27B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen_3_5_27B_A100\(80GB\).ipynb)
* [GLM-4.7-Flash](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/GLM_Flash_A100\(80GB\).ipynb)
* [gpt-oss-20b (contexte 500K)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt_oss_\(20B\)_500K_Context_Fine_tuning.ipynb)
* [Qwen3-30B-A3B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_MoE.ipynb)
* [notebook LoRA Nemotron-3-Nano-30B-A3B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Nemotron-3-Nano-30B-A3B_A100.ipynb)&#x20;
* [notebook GRPO Sudoku NeMo Gym](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/NeMo-Gym-Sudoku.ipynb)
* [Notebook GRPO multi-environnements NeMo Gym](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/NeMo-Gym-Multi-Environment.ipynb)
* [gpt-oss-120b](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(120B\)_A100-Fine-tuning.ipynb)
* [Qwen3 (32B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(32B\)_A100-Reasoning-Conversational.ipynb)
* [Llama 3.3 (70B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.3_\(70B\)_A100-Conversational.ipynb)
* [Gemma 3 (27B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(27B\)_A100-Conversational.ipynb)&#x20;
* [Baidu ERNIE 4.5 VL (28B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/ERNIE_4_5_VL_28B_A3B_PT_Vision.ipynb) - nouveau

### Autres notebooks importants :

* [**Agent de support client**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Granite4.0.ipynb)
* [Mistral Ministral 3](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Ministral_3_\(3B\)_Reinforcement_Learning_Sudoku_Game.ipynb) - nouveau (résolution du sudoku)
* [Déployer sur LM Studio ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\)-LMStudio.ipynb)- nouveau
* [Entraînement sensible à la quantification](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)_Instruct-QAT.ipynb) (QAT) - nouveau
* [Déploiement sur téléphone ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(0_6B\)-Phone_Deployment.ipynb)- nouveau
* [Raisonner avant **Appel d'outils** notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\).ipynb) - nouveau
* [Notebook Mobile Actions](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\)-Mobile-Actions.ipynb) - nouveau
* [**Création automatique des kernels**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) avec RL
* [**ModernBERT-large**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/bert_classification.ipynb) **- nouveau** 19 août
* [**Génération de données synthétiques Llama 3.2 (3B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Meta_Synthetic_Data_Llama3_2_\(3B\).ipynb)
* [gpt-oss-20b (contexte 500K)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt_oss_\(20B\)_500K_Context_Fine_tuning.ipynb) - nouveau (A100)
* [**Appel d'outils**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_Coder_\(1.5B\)-Tool_Calling.ipynb)
* [Mistral v0.3 Instruct (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-Conversational.ipynb)
* [Ollama](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_\(8B\)-Ollama.ipynb)
* [ORPO](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_\(8B\)-ORPO.ipynb)
* [Pré-entraînement continu](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-CPT.ipynb)
* [DPO Zephyr](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Zephyr_\(7B\)-DPO.ipynb)
* [***Inférence uniquement***](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_\(8B\)-Inference.ipynb)
* [Llama 3 (8B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_\(8B\)-Alpaca.ipynb)

### Notebooks pour cas d'usage spécifiques :

* [Déploiement sur téléphone ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(0_6B\)-Phone_Deployment.ipynb)- nouveau
* [Déployer sur LM Studio ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\)-LMStudio.ipynb)- nouveau
* [Raisonner avant **Appel d'outils**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\).ipynb) - nouveau
* [Mobile Actions](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\)-Mobile-Actions.ipynb) - nouveau
* [**Agent de support client**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Granite4.0.ipynb)
* [Entraînement sensible à la quantification](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)_Instruct-QAT.ipynb) (QAT) - nouveau
* [**Création automatique des kernels**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) avec RL **- nouveau**
* [DPO Zephyr](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Zephyr_\(7B\)-DPO.ipynb)
* [BERT - Classification de texte](https://colab.research.google.com/github/timothelaborie/text_classification_scripts/blob/main/unsloth_classification.ipynb) - (AutoModelForSequenceClassification)
* [Ollama](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_\(8B\)-Ollama.ipynb)
* [**Appel d'outils**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_Coder_\(1.5B\)-Tool_Calling.ipynb)
* [Pré-entraînement continu (CPT)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-CPT.ipynb)
* [Jeux de données multiples](https://colab.research.google.com/drive/1njCCbE1YVal9xC83hjdo2hiGItpY_D6t?usp=sharing) par Flail
* [KTO](https://colab.research.google.com/drive/1MRgGtLWuZX4ypSfGguFgC-IblTvO2ivM?usp=sharing) par Jeffrey
* [Interface de chat pour l'inférence](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Unsloth_Studio.ipynb)
* [Conversationnel](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.2_\(1B_and_3B\)-Conversational.ipynb)
* [ChatML](https://colab.research.google.com/drive/15F1xyn8497_dUbxZP4zWmPZ3PJx1Oymv?usp=sharing)
* [Complétion de texte](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_\(7B\)-Text_Completion.ipynb)

### Reste des notebooks :

* [Qwen2.5 (3B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_\(3B\)-GRPO.ipynb)
* [Gemma 2 (9B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma2_\(9B\)-Alpaca.ipynb)
* [Mistral NeMo (12B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_Nemo_\(12B\)-Alpaca.ipynb)
* [Phi-3.5 (mini)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_3.5_Mini-Conversational.ipynb)
* [Phi-3 (medium)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Phi_3_Medium-Conversational.ipynb)
* [Gemma 2 (2B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma2_\(2B\)-Alpaca.ipynb)
* [Qwen 2.5 Coder (14B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_Coder_\(14B\)-Conversational.ipynb)
* [Mistral Small (22B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_Small_\(22B\)-Alpaca.ipynb)
* [TinyLlama](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/TinyLlama_\(1.1B\)-Alpaca.ipynb)
* [CodeGemma (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/CodeGemma_\(7B\)-Conversational.ipynb)
* [Mistral v0.3 (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-Alpaca.ipynb)
* [Qwen2 (7B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2_\(7B\)-Alpaca.ipynb)

## Notebooks Kaggle

#### Notebooks standards :

* [**Gemma-4-31B** (Kaggle)](https://www.kaggle.com/code/danielhanchen/gemma4-31b-unsloth) - nouveau et **GRATUIT**
* [**gpt-oss (20B)**](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/notebooks/blob/main/nb/Kaggle-gpt-oss-\(20B\)-Fine-tuning.ipynb\&accelerator=nvidiaTeslaT4)
* [Gemma 3n (E4B)](https://www.kaggle.com/code/danielhanchen/gemma-3n-4b-multimodal-finetuning-inference)
* [Qwen3 (14B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Qwen3_\(14B\).ipynb)
* [Magistral-2509 (24B)](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/notebooks/blob/main/nb/Kaggle-Magistral_\(24B\)-Reasoning-Conversational.ipynb\&accelerator=nvidiaTeslaT4)
* [Gemma 3 (4B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Gemma3_\(4B\).ipynb)
* [Phi-4 (14B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Phi_4-Conversational.ipynb)
* [Llama 3.1 (8B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3.1_\(8B\)-Alpaca.ipynb)
* [Llama 3.2 (1B + 3B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3.2_\(1B_and_3B\)-Conversational.ipynb)
* [Qwen 2.5 (7B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Qwen2.5_\(7B\)-Alpaca.ipynb)

#### Notebooks GRPO (raisonnement) :

* [**Qwen2.5-VL**](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/notebooks/blob/main/nb/Kaggle-Qwen2_5_7B_VL_GRPO.ipynb\&accelerator=nvidiaTeslaT4) - GRPO Vision - nouveau
* [Qwen3 (4B)](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/notebooks/blob/main/nb/Kaggle-Qwen3_\(4B\)-GRPO.ipynb\&accelerator=nvidiaTeslaT4)
* [Gemma 3 (1B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Gemma3_\(1B\)-GRPO.ipynb)
* [Llama 3.1 (8B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3.1_\(8B\)-GRPO.ipynb)
* [Phi-4 (14B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Phi_4_\(14B\)-GRPO.ipynb)
* [Qwen 2.5 (3B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Qwen2.5_\(3B\)-GRPO.ipynb)

#### Notebooks de synthèse vocale (TTS) :

* [Sesame-CSM (1B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Sesame_CSM_\(1B\)-TTS.ipynb)
* [Orpheus-TTS (3B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Orpheus_\(3B\)-TTS.ipynb)
* [Whisper Large V3](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Whisper.ipynb) – Reconnaissance vocale
* [Llasa-TTS (1B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llasa_TTS_\(1B\).ipynb)
* [Spark-TTS (0.5B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Spark_TTS_\(0_5B\).ipynb)
* [Oute-TTS (1B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Oute_TTS_\(1B\).ipynb)

#### Notebooks Vision (multimodaux) :

* [Llama 3.2 Vision (11B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3.2_\(11B\)-Vision.ipynb)
* [Qwen 2.5-VL (7B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Qwen2.5_VL_\(7B\)-Vision.ipynb)
* [Pixtral (12B) 2409](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Pixtral_\(12B\)-Vision.ipynb)

#### Notebooks pour cas d'usage spécifiques :

* [Appel d'outils](https://www.kaggle.com/notebooks/welcome?src=https://github.com/unslothai/notebooks/blob/main/nb/Kaggle-Qwen2.5_Coder_\(1.5B\)-Tool_Calling.ipynb\&accelerator=nvidiaTeslaT4)
* [ORPO](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3_\(8B\)-ORPO.ipynb)
* [Pré-entraînement continu](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Mistral_v0.3_\(7B\)-CPT.ipynb)
* [DPO Zephyr](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Zephyr_\(7B\)-DPO.ipynb)
* [Inférence uniquement](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3.1_\(8B\)-Inference.ipynb)
* [Ollama](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Llama3_\(8B\)-Ollama.ipynb)
* [Complétion de texte](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Mistral_\(7B\)-Text_Completion.ipynb)
* [CodeForces-cot (raisonnement)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-CodeForces-cot-Finetune_for_Reasoning_on_CodeForces.ipynb)
* [Unsloth Studio (interface de chat)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Unsloth_Studio.ipynb)

#### Reste des notebooks :

* [Gemma 2 (9B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Gemma2_\(9B\)-Alpaca.ipynb)
* [Gemma 2 (2B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Gemma2_\(2B\)-Alpaca.ipynb)
* [CodeGemma (7B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-CodeGemma_\(7B\)-Conversational.ipynb)
* [Mistral NeMo (12B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Mistral_Nemo_\(12B\)-Alpaca.ipynb)
* [Mistral Small (22B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Mistral_Small_\(22B\)-Alpaca.ipynb)
* [TinyLlama (1.1B)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-TinyLlama_\(1.1B\)-Alpaca.ipynb)

Pour voir la liste complète de tous nos notebooks Kaggle, [cliquez ici](https://github.com/unslothai/notebooks#-kaggle-notebooks).

{% hint style="info" %}
N'hésitez pas à contribuer aux notebooks en visitant notre [dépôt](https://github.com/unslothai/notebooks)!
{% endhint %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://unsloth.ai/docs/fr/commencer/unsloth-notebooks.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.