Video-Pre-Training | Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos | Application Framework library

by openai Python Version: idm-model License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | Video-Pre-Training Summary

Video-Pre-Training is a Python library typically used in Server, Application Framework applications. Video-Pre-Training has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.

Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos

Support

Quality

Security

License

Reuse

Support

Video-Pre-Training has a medium active ecosystem.

It has 942 star(s) with 105 fork(s). There are 27 watchers for this library.

It had no major release in the last 12 months.

There are 6 open issues and 14 have been closed. On average issues are closed in 11 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Video-Pre-Training is idm-model

Quality

Video-Pre-Training has no bugs reported.

Security

Video-Pre-Training has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Video-Pre-Training is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Video-Pre-Training releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

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Video-Pre-Training Key Features

No Key Features are available at this moment for Video-Pre-Training.

Video-Pre-Training Examples and Code Snippets

No Code Snippets are available at this moment for Video-Pre-Training.

Community Discussions

Trending Discussions on Application Framework

What is meant by required-api: param name=”#target” in config.xml file of AGL widgets?

QUESTION

What is meant by required-api: param name=”#target” in config.xml file of AGL widgets?

Asked 2020-Mar-06 at 09:53

I am trying to understand various available AGL specific options that we can give in config.xml and I am referring to the link below

https://docs.automotivelinux.org/docs/en/halibut/apis_services/reference/af-main/2.2-config.xml.html

This is the sample config.xml file

...

ANSWER

Answered 2020-Mar-06 at 09:48

I figured out why we need this

required-api: param name="#target"

OPTIONAL(not compulsory)

It declares the name of the unit(in question it is main) requiring the listed apis. Only one instance of the param “#target” is allowed. When there is not instance of this param, it behave as if the target main was specified.

Source https://stackoverflow.com/questions/60561230

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Video-Pre-Training

You can download it from GitHub.
You can use Video-Pre-Training like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

This was a large effort by a dedicated team at OpenAI: Bowen Baker, Ilge Akkaya, Peter Zhokhov, Joost Huizinga, Jie Tang, Adrien Ecoffet, Brandon Houghton, Raul Sampedro, Jeff Clune The code here represents a minimal version of our model code which was prepared by Anssi Kanervisto and others so that these models could be used as part of the MineRL BASALT competition.

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