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egrace479zoeduanMatt Thompson
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Add pages on motivation to use Imageomics Org repos (#10)
* Add pages on motivation to use Imageomics Org repos Co-authored-by: Matt Thompson <[email protected]> Co-authored-by: Zoe Duan <[email protected]> * Remove question mark from page names * Fix nav to 'why use' pages --------- Co-authored-by: Zoe Duan <[email protected]> Co-authored-by: Matt Thompson <[email protected]>
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# _"Why should I put my work into the Imageomics GitHub org,"_ you ask?
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The [Imageomics GitHub organization](https://github.com/Imageomics) exists to facilitate collaboration and version control among team members working on projects within the institute and make them available to the research community. You are encouraged to take advantage of the benefits of using this GitHub organization for your institute projects!
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## Centralization
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This is the main aspect that leads to other benefits. Whether you are running your code on your own computer, a GPU server, a supercomputing cluster, AWS, or the Matrix, maintaining a git repository of this code hosted on the institute GitHub org keeps everyone's work that is otherwise scattered around in a single place. Some of the benefits derived from this are ...
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### Collaboration
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- You know where your team's work is, and your team knows where your work is.
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- Code is simpler to find, share, access, review, and manage.
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- Access privileges can be granted and managed through [teams](https://github.com/orgs/Imageomics/teams), which Institute staff can administer for you, rather than access having to be managed on a per-individual basis.
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- Progress can be communicated readily, and help can be solicited when needed, including through [teams](https://github.com/orgs/Imageomics/teams).
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### Knowledge Sharing
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- Projects documented by a well-written README file are much more accessible than combing through old Zoom recordings to find out or remember what someone else is working on.
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- When new members join, they can get up-to-speed quickly.
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- When members move on to new roles, their work is preserved and more easily continued and built upon.
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- Good practices can diffuse through and between teams more quickly.
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- These points enhance the research capacity and productivity of individuals as well as the overall institute.
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### Visibility + Impact
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- Work hosted under the Imageomics GitHub organization is directly associated with and contributes to the institute's brand, showcasing the collective contributions of our teams and enhancing the visibility and impact of their work within the broader community.
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- Your profile is featured alongside repositories you contribute to, providing opportunities for networking with those who find your work valuable.
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## Professional Development
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Despite its rough edges, the common standard for version control and code management is git. You'll get a competitive edge with experience using it on a team to collaborate.
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## Showcasing Your Work
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If you want your public work with Imageomics featured on your personal GitHub profile, you can make use of the GitHub [pin](https://docs.github.com/en/account-and-profile/setting-up-and-managing-your-github-profile/customizing-your-profile/pinning-items-to-your-profile) feature to have public repositories of your choice appear at the top of your profile whether they belong to you through an organization or personally.
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## Flexibility
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While we encourage you to host your institute-related work on the Imageomics GitHub organization to maximize these benefits, we understand that there may be situations where other platforms or private repositories are more appropriate. These include:
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- Personal projects or work not directly tied to the institute.
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- Projects developed prior to joining the institute where transferring ownership might be complex or undesirable.
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We strongly encourage you to keep your institute-related work centrally organized in the Imageomics GitHub organization to maximize the benefits for you and your fellow researchers!
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# _"Why should I put my work into the Imageomics Hugging Face org,"_ you ask?
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The [Imageomics Hugging Face organization](https://huggingface.co/imageomics) is a crucial resource for facilitating collaboration, sharing models, and enhancing the accessibility of our AI and machine learning projects. By utilizing the Imageomics Hugging Face organization, you can take full advantage of the following benefits:
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## Centralization
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Centralizing our models and datasets on the Imageomics Hugging Face organization ensures that all team members have a reliable source for the tools and resources they need. It helps to:
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- Keep everyone's work in a unified location, making it easier to manage and access.
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- Ensure consistency and reliability in the models and datasets used across different projects.
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## Collaboration
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Hugging Face provides robust tools for collaborative development, making it easier to:
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- Share models and datasets with your team and the wider research community.
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- Contribute to and improve upon the work of others.
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- Manage access through well-defined team structures, ensuring that the right people have the right permissions.
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- Request and provide feedback through integrated commenting and discussion features.
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## Knowledge Sharing
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By hosting models and datasets on Hugging Face, we enhance knowledge sharing within and beyond the institute. This includes:
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- Providing clear documentation and usage examples, making it easier for new members to get up to speed.
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- Facilitating the spread of best practices across teams and projects.
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## Visibility + Impact
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Work hosted on the Imageomics Hugging Face organization benefits from increased visibility and impact:
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- Models and datasets are directly associated with the Imageomics brand, showcasing our collective contributions.
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- Your contributions are highlighted on your profile, enhancing your professional reputation and networking opportunities.
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- High-quality, well-documented models and datasets can attract attention from the broader research community, leading to greater impact and potential collaborations.
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## Professional Development
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Using Hugging Face provides valuable experience with tools and practices that are widely recognized in the AI and machine learning communities. This includes:
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- Hands-on experience with state-of-the-art model hosting and deployment tools.
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- Opportunities to learn and implement best practices in model management and version control.
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## Showcasing Your Work
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Hugging Face offers several features to help you showcase your work:
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- You can highlight your contributions by pinning repositories to your profile, making your most significant work easily accessible.
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- Public models and datasets associated with the Imageomics organization can be featured on both your personal and the institute's profiles.
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## Flexibility
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While we encourage you to host your institute-related work on the Imageomics Hugging Face organization to maximize these benefits, we understand that there may be situations where other platforms or private repositories are more appropriate. These include:
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- Personal projects or work not directly tied to the institute.
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- Projects developed prior to joining the institute where transferring ownership might be complex or undesirable.
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We strongly encourage you to leverage the Imageomics Hugging Face organization for your institute-related projects. This will help you and your fellow researchers maximize collaboration, knowledge sharing, and the overall impact of our collective work.

mkdocs.yaml

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- "Projects Guide": wiki-guide/Guide-to-GitHub-Projects.md
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- "Branch Protections": wiki-guide/When-to-think-about-branch-protections.md
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- "Two Repo Problem": wiki-guide/Two-Repo-Problem.md
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- "Why Use the Institute GitHub": wiki-guide/Why-use-the-Institute-GitHub.md
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- Hugging Face Guide:
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- "Repo Guide": wiki-guide/Hugging-Face-Repo-Guide.md
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- "Workflow": wiki-guide/The-Hugging-Face-Workflow.md
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- "Dataset Upload Guide": wiki-guide/The-Hugging-Face-Dataset-Upload-Guide.md
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- "Why Use the Institute Hugging Face": wiki-guide/Why-use-the-Institute-Hugging-Face.md
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- Metadata Guide: wiki-guide/Metadata-Guide.md
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- Templates:
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- "Dataset Card Template": wiki-guide/HF_DatasetCard_Template_mkdocs.md

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