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A newer version of the Gradio SDK is available: 4.37.2

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Docker4ML

Useful docker scripts for ML developement. https://github.com/SimonLeeGit/Docker4ML

Build Docker Image

bash docker_build.sh

build_docker

Run Docker Container as Development Envirnoment

bash docker_run.sh

run_docker

Custom Docker Config

Config setup_env.sh

You can modify this file to custom your settings.

TAG=ml:dev
BASE_TAG=nvcr.io/nvidia/pytorch:23.12-py3

TAG

Your built docker image tag, you can set it as what you what.

BASE_TAG

The base docker image tag for your built docker image, here we use nvidia pytorch images. You can check it from https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch/tags

Also, you can use other docker image as base, such as: ubuntu

USER_NAME

Your user name used in docker container.

USER_PASSWD

Your user password used in docker container.

Config requriements.txt

You can add your default installed python libraries here.

transformers==4.27.1

By default, it has some libs installed, you can check it from https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-24-01.html

Config packages.txt

You can add your default apt-get installed packages here.

wget
curl
git

Config ports.txt

You can add some ports enabled for docker container here.

-p 6006:6006
-p 8080:8080

Config postinstallscript.sh

You can add your custom script to run when build docker image.

Q&A

If you have any use problems, please contact to simonlee235@gmail.com.