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Check out https://docs.docker.com/get-docker/ on information on how to install docker for your system.\n\n\n### Step - 2: NVIDIA docker runtime (not needed if you don't want to use GPUs)\n\nIf you have NVIDIA drivers installed, you need the NVIDIA runtime to use GPUs in the development environment.\nRun the following commands if you are on Ubuntu to set up the NVIDIA runtimes.\n\n```\n# Add the package repositories\ndistribution=$(. /etc/os-release;echo $ID$VERSION_ID)\ncurl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -\ncurl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list\n\nsudo apt-get update \u0026\u0026 sudo apt-get install -y nvidia-container-toolkit\nsudo systemctl restart docker\n```\n\nFor more information about the NVIDIA docker runtime, take a look here: https://github.com/NVIDIA/nvidia-docker\n\n### Step - 3: Build the container\n\n```\nmake build\n```\n\n### Step - 4: Start the coding environment\n\n```\nWORKSPACE=[PATH_TO_YOUR_CODEBASE] CPORT=[PORT] make code\n```\n\nWhere ```PATH_TO_YOUR_CODEBASE``` is the path to your code base where all the scripts/notebooks are located and ```PORT``` is the port you want to run the IDE on\n\ne.g. ```WORKSPACE=/home/abhishek/workspace/bert-sentiment CPORT=10012 make code```\n\n### Step - 5: Open the URL in broswer\n\n```http://127.0.0.1:10012/```\n\nAnd have fun coding!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhishekkrthakur%2Fml_dev_env","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabhishekkrthakur%2Fml_dev_env","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhishekkrthakur%2Fml_dev_env/lists"}