> 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/de/erste-schritte/unsloth-notebooks.md).

# Unsloth-Notebooks

Trainieren Sie Ihr eigenes Modell mit unseren Notebooks, unterstützt durch kostenlose GPU-Rechenleistung. Klicken Sie auf „Alle ausführen“ (oder speichern Sie lokal), fügen Sie Ihren Datensatz hinzu, trainieren Sie und stellen Sie bereit. Sie können jedes beliebige Modell in den Notebooks verwenden.

<a href="/pages/c96e3433e67c1b26226b1118128145a6ff8a990a#grpo-reasoning-rl" class="button secondary">GRPO (RL)</a><a href="/pages/c96e3433e67c1b26226b1118128145a6ff8a990a#text-to-speech-tts" class="button secondary">Text-zu-Sprache</a><a href="/pages/c96e3433e67c1b26226b1118128145a6ff8a990a#vision-multimodal" class="button secondary">Vision</a><a href="/pages/c96e3433e67c1b26226b1118128145a6ff8a990a#embedding-models" class="button secondary">Embedding</a><a href="/pages/c96e3433e67c1b26226b1118128145a6ff8a990a#kaggle-notebooks" class="button secondary">Kaggle</a>

Siehe auch unser GitHub-Repo für unsere Notebooks: [github.com/unslothai/notebooks](https://github.com/unslothai/notebooks/)

## Colab-Notebooks

**Wir stellen vor: unser** [**Unsloth Studio**](/docs/de/neu/studio.md)✨ **Notebook.** Modelle mit weniger als 22B Parametern trainieren und ausführen:

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

### Standard-SFT-Notebooks:

* [**Muse Glimmer (30B)**](/docs/de/modelle/muse-glimmer/train.md) **•** [Konversationell (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/de/modelle/gemma-4/train.md)**:** [E4B **(Vision)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(E4B\)-Vision.ipynb) **•** [E2B **(Text)**](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) **•** [**Inferenz**](https://colab.research.google.com/github/unslothai/unsloth/blob/main/studio/Unsloth_Studio_Colab.ipynb)
* [**Qwen3.5**](/docs/de/modelle/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) • [Inferenz](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/GPT_OSS_MXFP4_\(20B\)-Inference.ipynb) • [Fine-Tuning](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) • [Denken](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) • [Text](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) • [Text](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 (Reasoning RL):

* [**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) - neu
* [**Qwen3.5 (4B)**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_5_\(4B\)_Vision_GRPO.ipynb) - Vision GRPO
* [gpt-oss-20b](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) (automatische Erstellung von Kernen)
* [Mistral Ministral 3](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Ministral_3_\(3B\)_Reinforcement_Learning_Sudoku_Game.ipynb) (Sudoku lösen) - neu
* [Qwen3-8B - **FP8**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_8B_FP8_GRPO.ipynb) (L4) - neu
* [Llama-3.2-1B - **FP8**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama_FP8_GRPO.ipynb) (L4) - neu
* [gpt-oss-20b](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt_oss_\(20B\)_Reinforcement_Learning_2048_Game.ipynb) (2048-Spiel automatisch gewinnen)&#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) - Erweiterte 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-Beispiel)
* [DeepSeek-R1-0528-Qwen3 (8B)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/DeepSeek_R1_0528_Qwen3_\(8B\)_GRPO.ipynb) (für mehrsprachigen Anwendungsfall)
* [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) - Erweiterte 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 Multi-Agenten-Umgebung ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/NeMo-Gym-Multi-Environment.ipynb)(Mehrere agentische Umgebungen)

### Text-zu-Sprache (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) - Sprache-zu-Text (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)

**Sprache-zu-Text (SST):**

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

* [**Gemma 4**](/docs/de/modelle/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) - neu
* [**Qwen3.5**](/docs/de/modelle/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) - neu
* [**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 - neu
* [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

### Embedding-Modelle:

* [EmbeddingGemma (300M)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/EmbeddingGemma_\(300M\).ipynb) - neu
* [Qwen3-Embedding 4B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_Embedding_\(4B\).ipynb) - neu
* [Qwen3-Embedding 0,6B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_Embedding_\(0_6B\).ipynb) - neu
* [BGE M3](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/BGE_M3.ipynb) - neu
* [ModernBERT-large](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/bert_classification.ipynb) - neu
* [All-MiniLM-L6-v2](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/All_MiniLM_L6_v2.ipynb) - neu
* [GTE ModernBert](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/ModernBert.ipynb) - neu

### Große LLMs:

**Notebooks für große Modelle:** Diese überschreiten Colabs kostenlose 15-GB-VRAM-Stufe. Mit Colabs neuen 80-GB-GPUs können Sie Modelle mit 120B Parametern feinabstimmen.

{% hint style="info" %}
Ein Colab-Abonnement oder Guthaben ist erforderlich. Wir **verdienen** nichts an diesen Notebooks.
{% endhint %}

* [**Gemma-4-31B**](https://www.kaggle.com/code/danielhanchen/gemma4-31b-unsloth) - neu und **KOSTENLOS**
* [**DiffusionGemma**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/DiffusionGemma_\(26B-A4B\)-Sudoku.ipynb) - neu
* [Gemma-4-26B-A4B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(26B_A4B\)-Vision.ipynb) - neu
* [Gemma-4-31B](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma4_\(31B\)-Vision.ipynb) - neu
* [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 Kontext)](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-Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Nemotron-3-Nano-30B-A3B_A100.ipynb)&#x20;
* [NeMo Gym Sudoku GRPO-Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/NeMo-Gym-Sudoku.ipynb)
* [NeMo Gym Multi Environment GRPO-Notebook](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) - neu

### Weitere wichtige Notebooks:

* [**Kundenservice-Agent**](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) - neu (Sudoku lösen)
* [Auf LM Studio bereitstellen ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\)-LMStudio.ipynb)- neu
* [Quantisierungsbewusstes Training](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)_Instruct-QAT.ipynb) (QAT) - neu
* [Telefonbereitstellung ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(0_6B\)-Phone_Deployment.ipynb)- neu
* [Denken vor **Tool-Aufruf** Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\).ipynb) - neu
* [Mobile-Aktionen-Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\)-Mobile-Actions.ipynb) - neu
* [**Automatische Kernel-Erstellung**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) mit RL
* [**ModernBERT-large**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/bert_classification.ipynb) **- neu** 19. Aug.
* [**Generierung synthetischer Daten 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 Kontext)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt_oss_\(20B\)_500K_Context_Fine_tuning.ipynb) - neu (A100)
* [**Tool-Aufruf**](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)
* [Fortgesetztes Pretraining](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)
* [***Nur Inferenz***](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 für spezifische Anwendungsfälle:

* [Telefonbereitstellung ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(0_6B\)-Phone_Deployment.ipynb)- neu
* [Auf LM Studio bereitstellen ](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\)-LMStudio.ipynb)- neu
* [Denken vor **Tool-Aufruf**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\).ipynb) - neu
* [Mobile-Aktionen](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/FunctionGemma_\(270M\)-Mobile-Actions.ipynb) - neu
* [**Kundenservice-Agent**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Granite4.0.ipynb)
* [Quantisierungsbewusstes Training](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_\(4B\)_Instruct-QAT.ipynb) (QAT) - neu
* [**Automatische Kernel-Erstellung**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-\(20B\)-GRPO.ipynb) mit RL **- neu**
* [DPO Zephyr](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Zephyr_\(7B\)-DPO.ipynb)
* [BERT - Textklassifizierung](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)
* [**Tool-Aufruf**](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2.5_Coder_\(1.5B\)-Tool_Calling.ipynb)
* [Fortgesetztes Pretraining (CPT)](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_v0.3_\(7B\)-CPT.ipynb)
* [Mehrere Datensätze](https://colab.research.google.com/drive/1njCCbE1YVal9xC83hjdo2hiGItpY_D6t?usp=sharing) von Flail
* [KTO](https://colab.research.google.com/drive/1MRgGtLWuZX4ypSfGguFgC-IblTvO2ivM?usp=sharing) von Jeffrey
* [Inferenz-Chat-UI](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Unsloth_Studio.ipynb)
* [Konversationell](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)
* [Textvervollständigung](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Mistral_\(7B\)-Text_Completion.ipynb)

### Rest der 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 (mittel)](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-Notebooks

#### Standard-Notebooks:

* [**Gemma-4-31B** (Kaggle)](https://www.kaggle.com/code/danielhanchen/gemma4-31b-unsloth) - neu und **KOSTENLOS**
* [**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-(Reasoning)-Notebooks:

* [**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 - neu
* [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)

#### Text-zu-Sprache-(TTS)-Notebooks:

* [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) – Sprache-zu-Text
* [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)

#### Vision-(Multimodal)-Notebooks:

* [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 für spezifische Anwendungsfälle:

* [Tool-Aufruf](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)
* [Fortgesetztes Pretraining](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)
* [Nur Inferenz](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)
* [Textvervollständigung](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 (Reasoning)](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 (Chat-UI)](https://www.kaggle.com/notebooks/welcome?src=https%3A%2F%2Fgithub.com%2Funslothai/notebooks/blob/main/nb/Kaggle-Unsloth_Studio.ipynb)

#### Rest der 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)

Um eine vollständige Liste aller unserer Kaggle-Notebooks zu sehen, [hier klicken](https://github.com/unslothai/notebooks#-kaggle-notebooks).

{% hint style="info" %}
Sie können gern zu den Notebooks beitragen, indem Sie unser [Repo](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/de/erste-schritte/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.