mirror of https://github.com/InternLM/InternLM
59 lines
1.7 KiB
Markdown
59 lines
1.7 KiB
Markdown
## InternLM项目的依赖安装
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### 环境准备
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首先,需要安装的依赖包及对应版本列表如下:
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- Python == 3.10
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- GCC == 10.2.0
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- MPFR == 4.1.0
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- CUDA == 11.7
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- Pytorch == 1.13.1+cu117
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- Transformers >= 4.25.1
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- Flash-Attention == 23.05
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- Ampere或者Hopper架构的GPU (例如H100, A100)
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- Linux OS
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以上依赖包安装完成后,需要更新配置系统环境变量:
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```bash
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export CUDA_PATH={path_of_cuda_11.7}
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export GCC_HOME={path_of_gcc_10.2.0}
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export MPFR_HOME={path_of_mpfr_4.1.0}
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export LD_LIBRARY_PATH=${GCC_HOME}/lib64:${MPFR_HOME}/lib:${CUDA_PATH}/lib64:$LD_LIBRARY_PATH
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export PATH=${GCC_HOME}/bin:${CUDA_PATH}/bin:$PATH
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export CC=${GCC_HOME}/bin/gcc
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export CXX=${GCC_HOME}/bin/c++
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```
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### 环境安装
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将项目`internlm`及其依赖子模块,从 github 仓库中 clone 下来,命令如下:
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```bash
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git clone git@github.com:InternLM/InternLM.git --recurse-submodules
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```
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推荐使用 conda 构建一个 Python-3.10 的虚拟环境, 并基于`requirements/`文件安装项目所需的依赖包:
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```bash
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conda create --name internlm-env python=3.10 -y
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conda activate internlm-env
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cd internlm
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pip install -r requirements/torch.txt
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pip install -r requirements/runtime.txt
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```
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安装 flash-attention (version v1.0.5):
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```bash
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cd ./third_party/flash-attention
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python setup.py install
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cd ./csrc
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cd fused_dense_lib && pip install -v .
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cd ../xentropy && pip install -v .
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cd ../rotary && pip install -v .
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cd ../layer_norm && pip install -v .
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cd ../../../../
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```
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安装 Apex (version 23.05):
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```bash
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cd ./third_party/apex
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pip install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./
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cd ../../
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```
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