Label Studio for configurable data annotation
Create annotation projects for text, images, audio and other supported inputs.
AI GitHub
Explore AI projects, understand what they do and find something you can build with.
Showing 73–78 of 224 projects · Page 13 of 38
Argilla for collecting feedback on AI datasets
Define annotation records, fields and questions for people reviewing model outputs.
DagsHub Client for connecting ML projects to DagsHub
Connect Python experiment and data workflows to a DagsHub repository.
Aim for comparing training runs
Log experiment metrics and inspect curves and metadata across runs.
MLflow for tracking experiments and model artifacts
Record parameters, metrics and artifacts alongside model runs.
DVC for versioning datasets and ML pipelines
Track large artifacts and dependency-aware stages alongside a Git project.
AI GitHub Repos FAQ
What does an AI GitHub project page explain?
Each page introduces the project, explains its capabilities and highlights practical takeaways. Follow the repository link for the latest documentation and setup instructions.
How do I add a GitHub repository?
Sign in, choose Add Repo and paste the main URL of a public AI repository, not a file or issue link. Franklin AI uses the project’s README to build and publish a page and links your contribution to your profile. Each account can add up to 20 repositories a day.
What if a repository cannot be published straight away?
Private repositories cannot be added. If the README is too short for an automatic page, or the project is already being reviewed, the repository is saved in your submissions with the reason for an admin to complete, and you are credited when it is published.
What happens if the project is already listed?
Its existing page stays as it is. Adding it again links that page to your profile instead of creating a second one.
How do I find projects for one kind of work?
Use the Category filter. Each card shows its categories, such as AI Agents or AI Development, and the repository’s owner and name.