Qwen3.5 Update.md
Updated with Qwen3.5 Small models
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Michael Han
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README.md
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README.md
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@ -22,12 +22,11 @@ Notebooks are beginner friendly. Read our [guide](https://unsloth.ai/docs/get-st
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| Model | Free Notebooks | Performance | Memory use |
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|-----------|---------|--------|----------|
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| **gpt-oss (20B)** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-(20B)-Fine-tuning.ipynb) | 1.5x faster | 70% less |
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| **Qwen3.5 (4B)** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_5_(4B)_Vision.ipynb) | 1.5x faster | 60% less |
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| **gpt-oss (20B)** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-(20B)-Fine-tuning.ipynb) | 2x faster | 70% less |
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| **gpt-oss (20B): GRPO** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/gpt-oss-(20B)-GRPO.ipynb) | 2x faster | 80% less |
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| **Qwen3: Advanced GRPO** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_(4B)-GRPO.ipynb) | 2x faster | 50% less |
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| **Qwen3-VL (8B): GSPO** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_VL_(8B)-Vision-GRPO.ipynb) | 1.5x faster | 80% less |
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| **Gemma 3 (4B) Vision** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3_(4B)-Vision.ipynb) | 1.7x faster | 60% less |
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| **Gemma 3n (e4B)** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Gemma3N_(4B)-Conversational.ipynb) | 1.5x faster | 50% less |
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| **embeddinggemma (300M)** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/EmbeddingGemma_(300M).ipynb) | 2x faster | 20% less |
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| **Mistral Ministral 3 (3B)** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Ministral_3_VL_(3B)_Vision.ipynb) | 1.5x faster | 60% less |
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| **Llama 3.1 (8B) Alpaca** | [▶️ Start for free](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3.1_(8B)-Alpaca.ipynb) | 2x faster | 70% less |
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@ -54,7 +53,7 @@ For RTX 50x, B200, 6000 GPUs: `pip install unsloth`. Read our guides for: [Black
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To install Unsloth on **AMD** and **Intel** GPUs, follow our [AMD Guide](https://unsloth.ai/docs/get-started/install/amd) and [Intel Guide](https://unsloth.ai/docs/get-started/install/intel).
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## 🦥 Unsloth News
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- **Qwen3.5** including 35-A3B, 27B, 112B-A10B is now supported. [Guide + notebooks](https://unsloth.ai/docs/new/faster-moe)
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- **Qwen3.5** - 0.8B, 2B, 4B, 9B, 27B, 35-A3B, 112B-A10B are now supported. [Guide + notebooks](https://unsloth.ai/docs/models/qwen3.5/fine-tune)
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- Train **MoE LLMs 12x faster** with 35% less VRAM - DeepSeek, GLM, Qwen and gpt-oss. [Blog](https://unsloth.ai/docs/new/faster-moe)
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- **Embedding models**: Unsloth now supports ~1.8-3.3x faster embedding fine-tuning. [Blog](https://unsloth.ai/docs/new/embedding-finetuning) • [Notebooks](https://unsloth.ai/docs/get-started/unsloth-notebooks#embedding-models)
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- New **7x longer context RL** vs. all other setups, via our new batching algorithms. [Blog](https://unsloth.ai/docs/new/grpo-long-context)
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@ -125,25 +124,33 @@ pip install --upgrade --force-reinstall --no-cache-dir unsloth unsloth_zoo
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```
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See [here](#advanced-pip-installation) for advanced pip install instructions.
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### Windows Installation
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For this method, we will be utilizing Anaconda. You can view the [full guide with screenshots here](https://unsloth.ai/docs/get-started/install/windows-installation).
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1. **Install Miniconda (or Anaconda):** Miniconda is recommended. Install [Miniconda](https://www.anaconda.com/docs/getting-started/miniconda/install) or [Anaconda](https://www.anaconda.com/download), then open Anaconda PowerShell Prompt to continue.
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1. **Install NVIDIA Video Driver:**
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You should install the latest driver for your GPU. Download drivers here: [NVIDIA GPU Driver](https://www.nvidia.com/Download/index.aspx).
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2. **Create a Conda Environment:** Create and activate a fresh Python 3.12 environment for Unsloth.
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2. **Install Visual Studio C++:**
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You will need Visual Studio, with C++ installed. By default, C++ is not installed with [Visual Studio](https://visualstudio.microsoft.com/vs/community/), so make sure you select all of the C++ options. Also select options for Windows 10/11 SDK. For detailed instructions with options, see [here](https://unsloth.ai/docs/get-started/install/windows-installation#method-3-windows-directly).
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```bash
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conda create --name unsloth_env python==3.12 -y
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conda activate unsloth_env
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```
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3. **Install CUDA Toolkit:**
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Follow the instructions to install [CUDA Toolkit](https://developer.nvidia.com/cuda-toolkit-archive).
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3. **Check Your GPU and CUDA Version:** Run `nvidia-smi` to confirm that your NVIDIA GPU is detected and note the CUDA version shown in the output. If `nvidia-smi` does not work, reinstall the latest [NVIDIA drivers](https://www.nvidia.com/en-us/drivers/).
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4. **Install PyTorch:**
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You will need the correct version of PyTorch that is compatible with your CUDA drivers, so make sure to select them carefully.
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[Install PyTorch](https://pytorch.org/get-started/locally/).
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4. **Install PyTorch:** Install the Windows pip build of PyTorch that matches your CUDA version. Use [Install PyTorch](https://pytorch.org/get-started/locally/) to select the correct command for your system, then verify that PyTorch can see your GPU.
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5. **Install Unsloth:**
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```python
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pip install unsloth
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```
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```python
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import torch
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print(torch.cuda.is_available())
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A = torch.ones((10, 10), device="cuda")
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B = torch.ones((10, 10), device="cuda")
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A @ B
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```
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5. **Install Unsloth:** Only install Unsloth after PyTorch is working correctly.
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```bash
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pip install unsloth
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```
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#### Advanced/Troubleshooting
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For **advanced installation instructions** or if you see weird errors during installations:
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