# Unsloth ノートブック

無料のGPU計算を活用した当社のノートブックで、自分のモデルを学習できます。［Run all］をクリックするか、ローカルに保存して、データセットを追加し、学習して、デプロイしてください。ノートブック内の任意のモデルを使用できます。

<a href="/pages/a3325bc180768721f1119499c1b82e6d84e53794#grpo-reasoning-rl" class="button secondary">GRPO（RL）</a><a href="/pages/a3325bc180768721f1119499c1b82e6d84e53794#text-to-speech-tts" class="button secondary">テキスト読み上げ</a><a href="/pages/a3325bc180768721f1119499c1b82e6d84e53794#vision-multimodal" class="button secondary">ビジョン</a><a href="/pages/a3325bc180768721f1119499c1b82e6d84e53794#embedding-models" class="button secondary">埋め込み</a><a href="/pages/a3325bc180768721f1119499c1b82e6d84e53794#kaggle-notebooks" class="button secondary">Kaggle</a>

当社のノートブックについては、GitHubリポジトリもご覧ください: [github.com/unslothai/notebooks](https://github.com/unslothai/notebooks/)

## Colabノートブック

**新しくご紹介する** [**Unsloth Studio**](/docs/jp/xin-zhe/studio.md)✨ **ノートブック。** 22Bパラメータ未満のモデルを学習・実行:

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

### 標準SFTノートブック:

* [**Gemma 4**](/docs/jp/moderu/gemma-4/train.md)**:** [E4B **（ビジョン）**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(E4B\)-Vision.ipynb) **•** [E2B **（テキスト）**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(E2B\)-Text.ipynb) **•** [E2B **（音声）**](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) **•** [**推論**](https://colab.research.google.com/github/unslothai/unsloth/blob/main/studio/Unsloth_Studio_Colab.ipynb)
* [**Qwen3.5**](/docs/jp/moderu/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) • [推論](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/GPT_OSS_MXFP4_\(20B\)-Inference.ipynb) • [ファインチューニング](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) • [思考](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)-Thinking.ipynb) • [インストラクト](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) • [テキスト](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\).ipynb) • [ビジョン](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) • [テキスト](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_\(4B\)-Conversational.ipynb) • [ビジョン](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_\(4B\)-Vision.ipynb) • [音声](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（推論RL）:

* [**Qwen3.5（4B）**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_5_\(4B\)_Vision_GRPO.ipynb) - Vision GRPO - 新規
* [gpt-oss-20b](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) （自動カーネル作成）
* [Mistral Ministral 3](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Ministral_3_\(3B\)_Reinforcement_Learning_Sudoku_Game.ipynb) （数独を解く）- 新規
* [Qwen3-8B - **FP8**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_8B_FP8_GRPO.ipynb) （L4）- 新規
* [Llama-3.2-1B - **FP8**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama_FP8_GRPO.ipynb) （L4）- 新規
* [gpt-oss-20b](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt_oss_\(20B\)_Reinforcement_Learning_2048_Game.ipynb) （2048ゲームを自動で勝利）&#x20;
* [Qwen3-VL（8B）](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL_\(8B\)-Vision-GRPO.ipynb) - Vision GSPO
* [Qwen3（4B）](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)-GRPO.ipynb) - 高度なGRPO LoRA
* [Gemma 3（4B）](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\)-Vision-GRPO.ipynb) - Vision GSPO
* [gpt-oss-20b](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/OpenEnv_gpt_oss_\(20B\)_Reinforcement_Learning_2048_Game.ipynb) （2048 OpenEnvの例）
* [DeepSeek-R1-0528-Qwen3（8B）](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/DeepSeek_R1_0528_Qwen3_\(8B\)_GRPO.ipynb) （多言語ユースケース向け）
* [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) - 高度なGRPO LoRA
* [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)
* [NeMo Gym マルチエージェント環境 ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/NeMo-Gym-Multi-Environment.ipynb)（複数のエージェント環境）

### テキスト読み上げ（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) - 音声認識（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)

**音声認識（SST）:**

* [**Gemma 4（E2B）**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(E2B\)-Audio.ipynb) **- 音声 - 新規**
* [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) - 音声

### ビジョン（マルチモーダル）:

* [**Gemma 4**](/docs/jp/moderu/gemma-4/train.md)**:** [E2B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(E2B\)-Vision.ipynb) - 新規
* [**Qwen3.5**](/docs/jp/moderu/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) - 新規
* [**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) - Vision GSPO - 新規
* [Qwen2.5-VL](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2_5_7B_VL_GRPO.ipynb) - Vision GSPO
* [Gemma 3（4B）](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_\(4B\)-Vision-GRPO.ipynb) - Vision GSPO

### 埋め込みモデル:

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

### 大規模LLM:

**大規模モデル向けノートブック:** これらはColabの無料15GB VRAM枠を超えます。Colabの新しい80GB GPUを使えば、120Bパラメータのモデルをファインチューニングできます。

{% hint style="info" %}
Colabのサブスクリプションまたはクレジットが必要です。私たちは **一切** これらのノートブックから収益を得ていません。
{% endhint %}

* [**Gemma-4-31B** （Kaggle）](https://www.kaggle.com/code/danielhanchen/gemma4-31b-unsloth) - 新規で **無料**
* [Gemma-4-26B-A4B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(26B_A4B\)-Vision.ipynb) - 新規
* [Gemma-4-31B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(31B\)-Vision.ipynb) - 新規
* [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（500Kコンテキスト）](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)
* [Nemotron-3-Nano-30B-A3B LoRAノートブック](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Nemotron-3-Nano-30B-A3B_A100.ipynb)&#x20;
* [NeMo Gym 数独GRPOノートブック](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/NeMo-Gym-Sudoku.ipynb)
* [NeMo Gym マルチ環境GRPOノートブック](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) - 新規

### その他の重要なノートブック:

* [**カスタマーサポートエージェント**](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) - 新規（数独を解く）
* [LM Studioにデプロイ ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\)-LMStudio.ipynb)- 新規
* [量子化対応学習](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)_Instruct-QAT.ipynb) （QAT）- 新規
* [スマホ向けデプロイ ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(0_6B\)-Phone_Deployment.ipynb)- 新規
* [前に考える **ツール呼び出し** ノートブック](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\).ipynb) - 新規
* [モバイルアクション ノートブック](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\)-Mobile-Actions.ipynb) - 新規
* [**自動カーネル作成**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) RLで
* [**ModernBERT-large**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/bert_classification.ipynb) **- 新規** 8月19日
* [**合成データ生成 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（500Kコンテキスト）](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt_oss_\(20B\)_500K_Context_Fine_tuning.ipynb) - 新規（A100）
* [**ツール呼び出し**](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)
* [継続事前学習](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)
* [***推論のみ***](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)

### 特定ユースケース向けノートブック:

* [スマホ向けデプロイ ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(0_6B\)-Phone_Deployment.ipynb)- 新規
* [LM Studioにデプロイ ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\)-LMStudio.ipynb)- 新規
* [前に考える **ツール呼び出し**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\).ipynb) - 新規
* [モバイルアクション](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\)-Mobile-Actions.ipynb) - 新規
* [**カスタマーサポートエージェント**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Granite4.0.ipynb)
* [量子化対応学習](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)_Instruct-QAT.ipynb) （QAT）- 新規
* [**自動カーネル作成**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) RLで **- 新規**
* [DPO Zephyr](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Zephyr_\(7B\)-DPO.ipynb)
* [BERT - テキスト分類](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)
* [**ツール呼び出し**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_Coder_\(1.5B\)-Tool_Calling.ipynb)
* [継続事前学習（CPT）](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-CPT.ipynb)
* [複数データセット](https://colab.research.google.com/drive/1njCCbE1YVal9xC83hjdo2hiGItpY_D6t?usp=sharing) Flailによる
* [KTO](https://colab.research.google.com/drive/1MRgGtLWuZX4ypSfGguFgC-IblTvO2ivM?usp=sharing) Jeffreyによる
* [推論チャットUI](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Unsloth_Studio.ipynb)
* [会話型](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)
* [テキスト補完](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_\(7B\)-Text_Completion.ipynb)

### その他のノートブック:

* [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)

## Kaggleノートブック

#### 標準ノートブック:

* [**Gemma-4-31B** （Kaggle）](https://www.kaggle.com/code/danielhanchen/gemma4-31b-unsloth) - 新規で **無料**
* [**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)

#### GRPO（推論）ノートブック:

* [**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) - Vision GRPO - 新規
* [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)

#### テキスト読み上げ（TTS）ノートブック:

* [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) – 音声認識
* [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)

#### ビジョン（マルチモーダル）ノートブック:

* [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)

#### 特定ユースケース向けノートブック:

* [ツール呼び出し](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)
* [継続事前学習](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)
* [推論のみ](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)
* [テキスト補完](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（推論）](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（チャットUI）](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Unsloth_Studio.ipynb)

#### その他のノートブック:

* [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)

すべてのKaggleノートブックの完全一覧を見るには、 [こちらをクリック](https://github.com/unslothai/notebooks#-kaggle-notebooks).

{% hint style="info" %}
当社の [リポジトリ](https://github.com/unslothai/notebooks)!
{% endhint %}


---

# Agent Instructions: 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:

```
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The question should be specific, self-contained, and written in natural language.
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.