Source of the article | Hengyuan cloud community (focusing on artificial intelligence / deep learning cloud GPU server training platform, November favorite powder activity ing, official experience website:https://gpushare.com/ ）
Original address |https://gpushare.com/docs/ins…
After many periods of sharing, I believe many small partners have a certain understanding of the functions of our platform.
So, do you want to share instance, image and data with multiple people?
Today, let Xiaobian share with you how the team can better carry out fast and effective algorithm training on our platform ~
First, what is a team?
Multiple users can form a team, and users in a team can share instances and images with each other. To create a team, you first need a team leader to apply for qualification. After passing the qualification review, you can invite other users to join the team by sharing the team link.
Second, how to create a team?
Part1: Qualification Application
The application team leader needs to recharge up to 500 yuan and bind wechat. After meeting the conditions, select “team” my team “in the” team leader “console, and click” team leader “to apply to become the team leader.
Select the application information, confirm and submit it to the platform for approval.
Part2: management team
After passing the qualification review of the team leader, you can manage the team by selecting “team – my team” in “team leader”. Click # create a new team.
Enter the team name and click OK.
Click View team members in the team to manage the team members.
Copy the # member invitation link # to users who want to add to the team.
The user opens the link and can choose to join or reject according to requirements.
Finally, how to share resources?
In the # console, select # team – shared resources. Here, you can share instances or images with members of the whole team. Select the team and shared instance / image, and click {add shared instance / image.
Select the instance / image to share and click OK. Members of the team can see the shared resources.
The above is all the content shared today. In the new week, I wish everyone’s algorithm training to fly smoothly ~