this post was submitted on 05 Jun 2025
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Why is this 110MB though?
Because it stores the ML model. Everything is local
Thx for your answer, makes sense! I was already wondering how the recommendations are generated. Maybe you can put this in the readme as well? I think that will make it more clear what a user can expect.
Great idea, thank you for your feedback! I generated embeddings for repositories using a SVC model trained on a dataset containing almost all stars of Github. Recommendations are produced by finding the nearest neighbors in the resulting vectorial space. I might be improving this even further by including forks and watcher data in the future, but it's becoming expensive to train