EulerOS(NPU)安装llamafactory
一、系统环境
cat /etc/os-release
NAME="EulerOS"
VERSION="2.0 (SP10)"
ID="euleros"
VERSION_ID="2.0"
PRETTY_NAME="EulerOS 2.0 (SP10)"
ANSI_COLOR="0;31"uname -m
aarch64npu-smi info
# 8卡 ...
二、版本选择
- CANN 8.2.RC1
- torch 2.6.0
- torch-npu 2.6.0
三、安装CANN 8.2.RC1
1. 官方下载地址
wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/CANN/CANN%208.2.RC1/Ascend-cann-toolkit_8.2.RC1_linux-aarch64.runwget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/CANN/CANN%208.2.RC1/Ascend-cann-kernels-910b_8.2.RC1_linux-aarch64.run
2、root用户安装CANN方便所有用户使用这个版本
sh Ascend-cann-toolkit_8.2.RC1_linux-aarch64.run --check
sh Ascend-cann-toolkit_8.2.RC1_linux-aarch64.run --install
sh Ascend-cann-kernels-910b_8.2.RC1_linux-aarch64.run --check
sh Ascend-cann-kernels-910b_8.2.RC1_linux-aarch64.run --install
四、安装llamafactory
1. 创建新用户llamafactory
useradd -m -s /bin/bash llamafactory
passwd llamafactory
usermod -aG HwHiAiUser llamafactoryvisudo # /usr/local/Ascend权限llamafactory ALL=(ALL) NOPASSWD:ALL
su - llamafactory
2. 安装conda
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-aarch64.sh -O ~/miniconda.sh
bash ~/miniconda.sh -b -p $HOME/miniconda3
vim ~/.bashrcexport PATH=$HOME/miniconda3/bin:$PATH
conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/main
conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r
conda init
conda create -n lf310 python=3.10 -y
conda activate lf310
3. 配置环境变量cann多个版本并存（vim ~/.bashrc）
# cp /usr/local/Ascend/ascend-toolkit/set_env.sh
export LD_LIBRARY_PATH=/usr/local/Ascend/driver/lib64:/usr/local/Ascend/driver/lib64/common:/usr/local/Ascend/driver/lib64/driver
export ASCEND_TOOLKIT_HOME=/usr/local/Ascend/ascend-toolkit/8.2.RC1
export LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${ASCEND_TOOLKIT_HOME}/lib64/plugin/opskernel:${ASCEND_TOOLKIT_HOME}/lib64/plugin/nnengine:${ASCEND_TOOLKIT_HOME}/opp/built-in/op_impl/ai_core/tbe/op_tiling/lib/linux/$(arch):$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/tools/aml/lib64:${ASCEND_TOOLKIT_HOME}/tools/aml/lib64/plugin:$LD_LIBRARY_PATH
export PYTHONPATH=${ASCEND_TOOLKIT_HOME}/python/site-packages:${ASCEND_TOOLKIT_HOME}/opp/built-in/op_impl/ai_core/tbe:$PYTHONPATH
export PATH=${ASCEND_TOOLKIT_HOME}/bin:${ASCEND_TOOLKIT_HOME}/compiler/ccec_compiler/bin:${ASCEND_TOOLKIT_HOME}/tools/ccec_compiler/bin:$PATH
export ASCEND_AICPU_PATH=${ASCEND_TOOLKIT_HOME}
export ASCEND_OPP_PATH=${ASCEND_TOOLKIT_HOME}/opp
export TOOLCHAIN_HOME=${ASCEND_TOOLKIT_HOME}/toolkit
export ASCEND_HOME_PATH=${ASCEND_TOOLKIT_HOME}
4. gcc版本过低升级到8.4.0
- gcc版本
- 下载
wget https://mirrors.tuna.tsinghua.edu.cn/gnu/gcc/gcc-8.4.0/gcc-8.4.0.tar.gz - 解压
tar zxvf gcc-8.4.0.tar.gz - 下载依赖
./contrib/download_prerequisites - 创建编译文件夹
mkdir buildgcc && cd buildgcc - 编译安装 安装到/path 目录下 不要覆盖系统的gcc 否则安装其他软件会报permission 错误 需要指定 需要指定 CC
make CC=/path/gcc/bin/gccsudo mkdir -p /path sudo chown -R llamafactory:llamafactory /path # /path 目录下 方便其他用户该版本 ../configure -enable-checking=release -enable-languages=c,c++,fortran -disable-multilib --prefix=/path/gcc #make # 速度太慢改为并行编译 make -j$(nproc) # 大概1～2h make install # 这个很快 - 配置环境变量
#gcc export gcchome=/path/gcc export PATH=$gcchome/bin:$PATH export PATH=$gcchome/lib:$PATH export PATH=$gcchome/lib64:$PATH export LD_LIBRARY_PATH=$gcchome/lib:$LD_LIBRARY_PATH export LD_LIBRARY_PATH=$gcchome/lib64:$LD_LIBRARY_PATH export LIBRARY_PATH=$gcchome/lib:$LIBRARY_PATH export LIBRARY_PATH=$gcchome/lib64:$LIBRARY_PATH export PATH=$gcchome/include:$PATH export LD_LIBRARY_PATH=$gcchome/include:$LD_LIBRARY_PATH export LIBRARY_PATH=$gcchome/include:$LIBRARY_PATH
5、安装llamafactory
也可以参考llamafactory微调
conda activate lf310
pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install -e ".[torch-npu,metrics]" -i https://pypi.tuna.tsinghua.edu.cn/simple
pip show torch # 升级到2.6.0
pip uninstall torch torch-npu torchvision
pip install torch-npu==2.6.0 -i https://pypi.tuna.tsinghua.edu.cn/simple