## InternLM Installation ### Environment Preparation The required packages and corresponding version are shown as follows: - Python == 3.10 - GCC == 10.2.0 - MPFR == 4.1.0 - CUDA >= 11.7 - Pytorch >= 1.13.1 - Transformers >= 4.28.0 - Flash-Attention >= v1.0.5 - Apex == 23.05 - GPU with Ampere or Hopper architecture (such as H100, A100) - Linux OS After installing the above dependencies, some system environment variables need to be updated: ```bash export CUDA_PATH={path_of_cuda_11.7} export GCC_HOME={path_of_gcc_10.2.0} export MPFR_HOME={path_of_mpfr_4.1.0} export LD_LIBRARY_PATH=${GCC_HOME}/lib64:${MPFR_HOME}/lib:${CUDA_PATH}/lib64:$LD_LIBRARY_PATH export PATH=${GCC_HOME}/bin:${CUDA_PATH}/bin:$PATH export CC=${GCC_HOME}/bin/gcc export CXX=${GCC_HOME}/bin/c++ ``` ### Environment Installation Clone the project `internlm` and its dependent submodules from the github repository, as follows: ```bash git clone git@github.com:InternLM/InternLM.git --recurse-submodules ``` It is recommended to build a Python-3.10 virtual environment using conda and install the required dependencies based on the `requirements/` files: ```bash conda create --name internlm-env python=3.10 -y conda activate internlm-env cd internlm pip install -r requirements/torch.txt pip install -r requirements/runtime.txt ``` Install flash-attention (version v1.0.5): ```bash cd ./third_party/flash-attention python setup.py install cd ./csrc cd fused_dense_lib && pip install -v . cd ../xentropy && pip install -v . cd ../rotary && pip install -v . cd ../layer_norm && pip install -v . cd ../../../../ ``` Install Apex (version 23.05): ```bash cd ./third_party/apex pip install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./ cd ../../ ``` ### Environment Image Users can use the provided dockerfile combined with docker.Makefile to build their own images, or obtain images with InternLM runtime environment installed from https://hub.docker.com/r/internlm/internlm. #### Image Configuration and Build The configuration and build of the Dockerfile are implemented through the docker.Makefile. To build the image, execute the following command in the root directory of InternLM: ``` bash make -f docker.Makefile BASE_OS=centos7 ``` In docker.Makefile, you can customize the basic image, environment version, etc., and the corresponding parameters can be passed directly through the command line. For BASE_OS, ubuntu20.04 and centos7 are respectively supported. #### Pull Standard Image The standard image based on ubuntu and centos has been built and can be directly pulled: ```bash # ubuntu20.04 docker pull internlm/internlm:torch1.13.1-cuda11.7.1-flashatten1.0.5-ubuntu20.04 # centos7 docker pull internlm/internlm:torch1.13.1-cuda11.7.1-flashatten1.0.5-centos7 ``` #### Run Container For the local standard image built with dockerfile or pulled, use the following command to run and enter the container: ```bash docker run --gpus all -it -m 500g --cap-add=SYS_PTRACE --cap-add=IPC_LOCK --shm-size 20g --network=host --name myinternlm internlm/internlm:torch1.13.1-cuda11.7.1-flashatten1.0.5-centos7 bash ``` The default directory in the container is `/InternLM`, please start training according to the [Usage](./usage.md).