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GPU Utilization in Containerized Environments: A Comprehensive Guide #25
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I can't review until you implement the checklist. Please read closely README. Some repeated problems from other PR's are present also. Current status of the article is 2.5/10. inadequate effort invested. |
I'm sorry for making your work difficult. I thought the checklist was to be used by you in your review hence the reason I ignored it. I'm making the necessary corrections now. |
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Have you tested this?
This is 5/10.
Some serious errors, especially regarding Daytona. User need to be able to use the code and run it.
Share the code on your github repo, create a starter-gpu repo with all needed files to create a GPU enabled workspace in Daytona
#### Cloning the nanoGPT Repository | ||
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Start by cloning the nanoGPT repository from GitHub: | ||
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When using Daytona, daytona is cloning the repo adn creating workspace out of it inside the docker container
articles/20240820_gpu_utilisation.md
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This Dockerfile sets up the environment required to run nanoGPT, including CUDA and PyTorch, which are essential for leveraging GPU resources. | ||
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where devcontainer? please add
Example command: | ||
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```bash | ||
daytona run --gpus all nanogpt-gpu |
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this is halucination?!
@JohnnieJnr is this true? Running nanoGPT in DaytonaDaytona is a container orchestration platform that simplifies running containerized applications, especially those requiring GPU support. To run nanoGPT in Daytona, follow these steps: |
Please close this PR and fix all the changes. |
@JohnnieJnr where are we with this? |
@nkkko I'm working on rewriting the article. I'll submit the first revision by Thursday |
Signed-off-by: JohnnieJnr <[email protected]>
Signed-off-by: JohnnieJnr <[email protected]>
Signed-off-by: JohnnieJnr <[email protected]>
Signed-off-by: JohnnieJnr <[email protected]>
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@JohnnieJnr you have attempted 2 other issues and have 2 other open PRs. |
@JohnnieJnr i'm closing this PR as you have another open one that is assigned to you. |
/claim #8
/closed #8
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