User: 你是哪个版本
Assistant: 我是OpenAI的GPT-4版本。有什么我可以帮助你的吗？
User: 4o吗
Assistant: 我是GPT-4，并不是具体的更新版本“4o”。如果有任何问题或需要帮助的地方，请随时告诉我！
User: 你是哪个版本
Assistant: 我是基于OpenAI的GPT-4技术的语言模型，但我没有提供具体子版本号的信息。如果你有任何问题或者需要帮助的地方，请随时告诉我！
User: Resolved an issue affecting the image_models property.


啥意思
Assistant: 这句话通常是在软件更新或错误修复的日志中看到的，意思是修复了与`image_models`属性相关的问题。`image_models`可能指的是一个软件系统中的图像处理模块或模型，所以这个修复可能涉及到提高图像处理的准确性、性能或稳定性。如果你有关于这个修复的更多具体问题或者需要进一步的信息，请提供更多的背景资料，我会尽力帮助你。
User: PyPI version Build Status

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udocker is a basic user tool to execute simple docker containers in user space without requiring root privileges. Enables download and execution of docker containers by non-privileged users in Linux systems where docker is not available. It can be used to pull and execute docker containers in Linux batch systems and interactive clusters that are managed by other entities such as grid infrastructures or externally managed batch or interactive systems.

udocker does not require any type of privileges nor the deployment of services by system administrators. It can be downloaded and executed entirely by the end user. The limited root functionality provided by some of the udocker execution modes is either simulated or provided via user namespaces.

udocker is a wrapper around several tools and libraries to mimic a subset of the docker capabilities including pulling images and running containers with minimal functionality.

Important notice: We have changed the udocker tools location as of udocker 1.3.17. This affects the configuration option conf['tarball'] and environment variable UDOCKER_TARBALL, so if you are using udocker <= 1.3.16, make sure to: export UDOCKER_TARBALL=https://download.a.incd.pt/udocker/udocker-englib-1.2.11.tar.gz.

Documentation
The full documentation is available at:

udocker documentation
Installation manual
User manual
Reference card
How does it work
udocker is written in Python, it has a minimal set of dependencies so that can be executed in a wide range of Linux systems.

udocker does not make use of docker nor requires its presence.

udocker "executes" the containers by simply providing a chroot like environment over the extracted container. The current implementation supports different methods to mimic chroot thus enabling execution of containers under a chroot like environment without requiring privileges. udocker transparently supports several methods to execute the containers based on external tools and libraries such as:

PRoot
Fakechroot
runc
crun
Singularity
With the exception of Singularity the tools and libraries to support execution are downloaded and deployed by udocker during the installation process. This installation is performed in the user home directory and does not require privileges. The udocker related files such as libraries, executables, documentation, licenses, container images and extracted directory trees are placed by default under $HOME/.udocker.

Advantages
Can be deployed by the end-user
Does not require privileges for installation
Does not require privileges for execution
Does not require compilation, just transfer the Python code
Encapsulates several tools and execution methods
Includes the required tools already statically compiled to work across systems
Provides a docker like command line interface
Supports a subset of docker commands: search, pull, import, export, load, save, login, logout, create and run
Understands docker container metadata
Allows loading of docker and OCI containers
Supports NVIDIA GPGPU applications
Can execute in systems and environments where Linux namespaces support is unavailable
Runs both on new and older Linux distributions including: CentOS 6, CentOS 7, CentOS 8, Ubuntu 14, Ubuntu 16, Ubuntu 18, Ubuntu 20, Ubuntu 21, Alpine, Fedora, etc
Python 2 and Python 3
Since v1.3.0, udocker supports Python 2.7 and Python >= 3.6. The original udocker v1.1.x for Python 2 is no longer maintained but is still available here.

Syntax
        Commands:
          search <repo/expression>      :Search dockerhub for container images
          pull <repo/image:tag>         :Pull container image from dockerhub
          create <repo/image:tag>       :Create container from a pulled image
          run <container>               :Execute container
          run <repo/image:tag>          :Pull, create and execute container

          images -l                     :List container images
          ps -m -s                      :List created containers
          name <container_id> <name>    :Give name to container
          rmname <name>                 :Delete name from container
          rename <name> <new_name>      :Change container name
          clone <container_id>          :Duplicate container
          rm <container-id>             :Delete container
          rmi <repo/image:tag>          :Delete image
          tag <repo/image:tag> <repo2/image2:tag2> :Tag image

          import <tar> <repo/image:tag> :Import tar file (exported by docker)
          import - <repo/image:tag>     :Import from stdin (exported by docker)
          export -o <tar> <container>   :Export container directory tree
          export - <container>          :Export container directory tree
          load -i <imagefile>           :Load image from file (saved by docker)
          load                          :Load image from stdin (saved by docker)
          save -o <imagefile> <repo/image:tag>  :Save image with layers to 



这是什么项目如何部署
Assistant: