| # Slime NPU Patch Installation Guide |
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| This guide provides instructions for installing Slime with NPU support, including all required dependencies and patches. |
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| ## Component Version Mapping |
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| | Component | Version/Commit | Source | |
| | --------------- | ---------------------------------------- | ------------------------------------------------------------------------------------------------------------------- | |
| | Slime | v0.2.2 | [GitHub](https://github.com/THUDM/slime/tree/v0.2.2) | |
| | SGLang | dce8b0606c06d3a191a24c7b8cbe8e238ab316c9 | [GitHub](https://github.com/sgl-project/sglang/tree/sglang-slime) | |
| | SGL Kernel NPU | 2026.02.01 | [GitHub](https://github.com/sgl-project/sgl-kernel-npu/releases/tag/2026.02.01) | |
| | Megatron-Bridge | 35b4ebfc486fb15dcc0273ceea804c3606be948a | [GitHub](https://github.com/fzyzcjy/Megatron-Bridge) | |
| | Megatron-LM | 3714d81d418c9f1bca4594fc35f9e8289f652862 | [GitHub](https://github.com/NVIDIA/Megatron-LM) | |
| | MindSpeed | fc63de5c48426dd019c3b3f39e65f5bdf56e4086 | [GitCode](https://gitcode.com/Ascend/MindSpeed) | |
| | HDK | 25.3.RC1 | [Ascend](https://www.hiascend.com/hardware/firmware-drivers/commercial?product=7\&model=33) | |
| | CANN | 8.5.0 | [Ascend](https://www.hiascend.com/developer/download/community/result?module=cann\&cann=8.5.0\&product=7\&model=33) | |
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| ## Preparing the Running Environment |
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| ### Python Version |
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| Only `python==3.11` is supported currently. |
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| ```shell |
| conda create -n slime_release python=3.11 |
| conda activate slime_release |
| ``` |
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| ### Working Directory Setup |
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| ```shell |
| mkdir <WORKSPACE> && cd <WORKSPACE> |
| ``` |
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| ### CANN Environment |
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| Prior to start work with Slime on Ascend you need to install CANN Toolkit, Kernels operator package and NNAL version 8.5.0, check the [installation guide](https://www.hiascend.com/document/detail/zh/CANNCommunityEdition/83RC1/softwareinst/instg/instg_0008.html?Mode=PmIns\&InstallType=local\&OS=openEuler\&Software=cannToolKit) |
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| ```shell |
| source <CANN_PATH>/ascend-toolkit/set_env.sh |
| source <CANN_PATH>/nnal/atb/set_env.sh |
| ``` |
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| ### PyTorch and PyTorch NPU |
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| ```shell |
| pip install torch-npu==2.8.0 |
| ``` |
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| ## Installing Dependencies |
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| ### SGLang |
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| ```shell |
| cd <WORKSPACE> |
| git clone https://github.com/sgl-project/sglang.git && cd sglang |
| git checkout dce8b0606c06d3a191a24c7b8cbe8e238ab316c9 |
| mv python/pyproject.toml python/pyproject.toml.backup |
| mv python/pyproject_other.toml python/pyproject.toml |
| pip install -e "python[srt_npu]" |
| pip install torch-npu==2.8.0 |
| ``` |
|
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| ### SGL Kernel NPU and Torch Memory Saver |
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| Download `sgl-kernel-npu-2026.02.01-torch2.8.0-py311-cann8.5.0-a3-aarch64.zip` from the release link, then install: |
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| ```shell |
| pip install sgl_kernel_npu-2026.2.1-cp311-cp311-linux_aarch64.whl |
| pip install torch_memory_saver-0.0.8-cp311-cp311-linux_aarch64.whl |
| ``` |
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| ### Megatron-Bridge |
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| ```shell |
| pip install git+https://github.com/ISEEKYAN/mbridge.git@89eb10887887bc74853f89a4de258c0702932a1c --no-deps |
| |
| cd <WORKSPACE> |
| git clone https://github.com/fzyzcjy/Megatron-Bridge.git -b dev_rl |
| pip install nvidia-modelopt[torch]>=0.37.0 --no-build-isolation |
| ``` |
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| ### Megatron-LM |
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| ```shell |
| cd <WORKSPACE> |
| git clone https://github.com/NVIDIA/Megatron-LM.git --recursive && \ |
| cd Megatron-LM/ && git checkout 3714d81d418c9f1bca4594fc35f9e8289f652862 && \ |
| pip install -e . |
| ``` |
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| ### MindSpeed |
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| ```shell |
| cd <WORKSPACE> |
| git clone https://gitcode.com/Ascend/MindSpeed.git && \ |
| cd MindSpeed/ && git checkout fc63de5c48426dd019c3b3f39e65f5bdf56e4086 && \ |
| pip install -e . |
| ``` |
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| ### Slime |
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| ```shell |
| cd <WORKSPACE> |
| git clone https://github.com/ascend-slime/slime.git && cd slime |
| cp -r docker/npu_patch ../npu_patch |
| git checkout v0.2.2 |
| pip install -e . |
| ``` |
|
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| ## Applying Patches |
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| ```shell |
| cd <WORKSPACE>/slime |
| git apply ../npu_patch/slime.patch |
| |
| cd <WORKSPACE>/sglang |
| git apply ../slime/docker/patch/v0.5.7/sglang.patch |
| git apply ../npu_patch/sglang.patch |
| |
| cd <WORKSPACE>/Megatron-LM |
| git apply ../slime/docker/patch/v0.5.7/megatron.patch |
| git apply ../npu_patch/megatron.patch |
| |
| cd <WORKSPACE>/Megatron-Bridge |
| git apply ../npu_patch/megatron-bridge.patch |
| |
| cd <WORKSPACE>/MindSpeed |
| git apply ../npu_patch/mindspeed.patch |
| ``` |
|
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| ## Additional Dependencies |
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| ```shell |
| cd <WORKSPACE>/slime |
| pip install triton-ascend |
| pip install torch-npu==2.8.0 |
| pip install torchvision==0.23.0 |
| pip install numpy==1.26.0 |
| ``` |
|
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| ## Running the Training |
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| ### Configuration |
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| Modify the paths in the following files according to your environment (note to use your CANN version): |
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| **Common (both GRPO and PPO):** |
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| - `slime/utils/external_utils/command_utils.py` |
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| **GRPO:** |
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| - `examples/geo3k_vlm_multi_turn/run_grpo_npu.sh` |
| - `examples/geo3k_vlm_multi_turn/run_geo3k_vlm_multi_turn_grpo_npu.py` |
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| **PPO:** |
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| - `examples/geo3k_vlm_multi_turn/run_ppo_npu.sh` |
| - `examples/geo3k_vlm_multi_turn/run_geo3k_vlm_multi_turn_ppo_npu.py` |
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| ### Dataset |
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| Download the dataset from [HuggingFace](https://huggingface.co/datasets/VeraIsHere/geo3k_imgurl_processed) following the instructions in the script directory. |
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| ### Execute Training |
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| ```shell |
| cd <WORKSPACE>/slime |
| # GRPO |
| bash examples/geo3k_vlm_multi_turn/run_grpo_npu.sh |
| # PPO |
| bash examples/geo3k_vlm_multi_turn/run_ppo_npu.sh |
| ``` |
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| To save logs and display them simultaneously: |
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| ```shell |
| # GRPO |
| bash examples/geo3k_vlm_multi_turn/run_grpo_npu.sh 2>&1 | tee -a <LOG_FILE> |
| # PPO |
| bash examples/geo3k_vlm_multi_turn/run_ppo_npu.sh 2>&1 | tee -a <LOG_FILE> |
| ``` |
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| ## Placeholders Reference |
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| | Placeholder | Description | Example | |
| | ------------- | ------------------------------------ | --------------------- | |
| | `<WORKSPACE>` | Root directory for all installations | `/root/slime-release` | |
| | `<CANN_PATH>` | Path to CANN installation directory | `/usr/local/ascend` | |
| | `<LOG_FILE>` | Path to log file for training output | `training.log` | |
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