### Unsloth Zoo - Utils for Unsloth!
✨ Finetune for Free
All notebooks are beginner friendly! Add your dataset, click "Run All", and you'll get a 2x faster finetuned model which can be exported to GGUF, Ollama, vLLM or uploaded to Hugging Face.
| Unsloth supports | Free Notebooks | Performance | Memory use |
|---|---|---|---|
| Llama 3.2 (3B) | ▶️ Start for free | 2x faster | 60% less |
| Llama 3.1 (8B) | ▶️ Start for free | 2x faster | 60% less |
| Phi-3.5 (mini) | ▶️ Start for free | 2x faster | 50% less |
| Gemma 2 (9B) | ▶️ Start for free | 2x faster | 63% less |
| Mistral Small (22B) | ▶️ Start for free | 2x faster | 60% less |
| Ollama | ▶️ Start for free | 1.9x faster | 43% less |
| Mistral v0.3 (7B) | ▶️ Start for free | 2.2x faster | 73% less |
| ORPO | ▶️ Start for free | 1.9x faster | 43% less |
| DPO Zephyr | ▶️ Start for free | 1.9x faster | 43% less |
- Kaggle Notebooks for Llama 3.1 (8B), Gemma 2 (9B), Mistral (7B)
- Run Llama 3.2 1B 3B notebook and Llama 3.2 conversational notebook
- Run Llama 3.1 conversational notebook and Mistral v0.3 ChatML
- This text completion notebook is for continued pretraining / raw text
- This continued pretraining notebook is for learning another language
- Click here for detailed documentation for Unsloth.
🔗 Links and Resources
| Type | Links |
|---|---|
| 📚 Documentation & Wiki | Read Our Docs |
 Twitter (aka X) |
Follow us on X |
| 💾 Installation | unsloth/README.md |
| 🥇 Benchmarking | Performance Tables |
| 🌐 Released Models | Unsloth Releases |
| ✍️ Blog | Read our Blogs |
⭐ Key Features
- All kernels written in OpenAI's Triton language. Manual backprop engine.
- 0% loss in accuracy - no approximation methods - all exact.
- No change of hardware. Supports NVIDIA GPUs since 2018+. Minimum CUDA Capability 7.0 (V100, T4, Titan V, RTX 20, 30, 40x, A100, H100, L40 etc) Check your GPU! GTX 1070, 1080 works, but is slow.
- Works on Linux and Windows via WSL.
- Supports 4bit and 16bit QLoRA / LoRA finetuning via bitsandbytes.
- Open source trains 5x faster - see Unsloth Pro for up to 30x faster training!
- If you trained a model with 🦥Unsloth, you can use this cool sticker!
💾 Installation Instructions
These are utilities for Unsloth, so install Unsloth as well! For stable releases for Unsloth Zoo, use pip install unsloth_zoo. We recommend pip install "unsloth_zoo @ git+https://github.com/unslothai/unsloth-zoo.git" for most installations though.
pip install unsloth_zooLicense
Unsloth Zoo is licensed under the GNU Affero General Public License.