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@ -46,7 +46,7 @@ pip install unsloth
For Windows, `pip install unsloth` works only if you have Pytorch installed. Read our [Windows Guide](https://docs.unsloth.ai/get-started/installing-+-updating/windows-installation).
### Docker
Use our official [Unsloth Docker image](https://hub.docker.com/r/unsloth/unsloth) ```unsloth/unsloth``` container. Read our [Docker Guide](https://docs.unsloth.ai/get-started/install-and-update/docker).
### Blackwell
### Blackwell & DGX Spark
For RTX 50x, B200, 6000 GPUs, simply do `pip install unsloth`. Read our [Blackwell Guide](https://docs.unsloth.ai/basics/training-llms-with-blackwell-rtx-50-series-and-unsloth) for more details.
## 🦥 Unsloth.ai News
@ -80,21 +80,21 @@ For RTX 50x, B200, 6000 GPUs, simply do `pip install unsloth`. Read our [Blackwe
## 🔗 Links and Resources
| Type | Links |
| ------------------------------- | --------------------------------------- |
| <img width="15" src="https://redditinc.com/hs-fs/hubfs/Reddit%20Inc/Brand/Reddit_Logo.png" />&nbsp; **r/unsloth Reddit** | [Join Reddit community](https://reddit.com/r/unsloth)|
| 📚 **Documentation & Wiki** | [Read Our Docs](https://docs.unsloth.ai) |
| <img width="16" src="https://upload.wikimedia.org/wikipedia/commons/6/6f/Logo_of_Twitter.svg" />&nbsp; **Twitter (aka X)** | [Follow us on X](https://twitter.com/unslothai)|
| 💾 **Installation** | [Pip install](https://docs.unsloth.ai/get-started/installing-+-updating)|
| 🔮 **Our Models** | [Unsloth Releases](https://docs.unsloth.ai/get-started/all-our-models)|
| 💾 **Installation** | [Pip & Docker Install](https://docs.unsloth.ai/get-started/installing-+-updating)|
| 🔮 **Our Models** | [Unsloth Catalog](https://docs.unsloth.ai/get-started/all-our-models)|
| ✍️ **Blog** | [Read our Blogs](https://unsloth.ai/blog)|
| <img width="15" src="https://redditinc.com/hs-fs/hubfs/Reddit%20Inc/Brand/Reddit_Logo.png" />&nbsp; **Reddit** | [Join our Reddit](https://reddit.com/r/unsloth)|
## ⭐ Key Features
- Supports **full-finetuning**, pretraining, 4b-bit, 16-bit and **8-bit** training
- Supports **all models** including [TTS](https://docs.unsloth.ai/basics/text-to-speech-tts-fine-tuning), multimodal, [BERT](https://docs.unsloth.ai/get-started/unsloth-notebooks#other-important-notebooks) and more! Any model that works in transformers, works in Unsloth.
- The most efficient library for [Reinforcement Learning (RL)](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide), using 80% less VRAM. Supports GRPO, GSPO, DrGRPO, DAPO etc.
- **0% loss in accuracy** - no approximation methods - all exact.
- All kernels written in [OpenAI's Triton](https://openai.com/index/triton/) language. Manual backprop engine.
- Supports NVIDIA (since 2018), AMD and Intel GPUs. Minimum CUDA Capability 7.0 (V100, T4, Titan V, RTX 20, 30, 40x, A100, H100, L40 etc)
- Supports NVIDIA (since 2018), AMD and Intel GPUs and DGX Spark. Minimum CUDA Capability 7.0 (V100, T4, Titan V, RTX 20, 30, 40x, A100, H100, L40 etc)
- Works on **Linux**, WSL and **Windows**
- All kernels written in [OpenAI's Triton](https://openai.com/index/triton/) language. Manual backprop engine.
- If you trained a model with 🦥Unsloth, you can use this cool sticker! &nbsp; <img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/made with unsloth.png" width="200" align="center" />
## 💾 Install Unsloth
@ -351,8 +351,10 @@ trainer.train()
<a name="RL"></a>
## 💡 Reinforcement Learning
RL including GRPO, GSPO, DrGRPO, DAPO, PPO, Reward Modelling, Online DPO all work with Unsloth. List of RL notebooks:
[RL](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide) including [GRPO](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide#training-with-grpo), [GSPO](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/gspo-reinforcement-learning), DrGRPO, DAPO, PPO, Reward Modelling, Online DPO all work with Unsloth.
Read our [Reinforcement Learning Guide](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide) or our [advanced RL docs](https://docs.unsloth.ai/get-started/reinforcement-learning-rl-guide/advanced-rl-documentation) for batching, generation & training parameters.
List of RL notebooks:
- gpt-oss GSPO notebook: [Link](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-(20B)-GRPO.ipynb)
- Qwen2.5-VL GSPO notebook: [Link](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen2_5_7B_VL_GRPO.ipynb)
- Advanced Qwen3 GRPO notebook: [Link](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_(4B)-GRPO.ipynb)