[ml] gitmodel

[Undescribed Horrific Abuse, One Victim & Survivor of Many]

haven’t really looked at it, but the blurb mentions self recursion a little

https://www.reddit.com/r/MachineLearning/comments/11o97on/p_gitmodel_dynamically_generate_highquality/

[P] GITModel: Dynamically generate high-quality hierarchical topic
tree representations of GitHub repositories using customizable GNN
message passing layers, chatgpt, and topic modeling.

Decompose Python libraries and generate Coherent hierarchical topic
models of the repository.
https://github.com/danielpatrickhug/GitModel
The ability to bootstrap its own codebase is a powerful feature as it
allows for efficient self-improvement and expansion. It means that the
codebase is designed in such a way that it can use its own output as
an input to improve itself. In the context of GitModel, this feature
allows for the efficient improvement and expansion of its own
codebase. By using its own output to generate hierarchical topic trees
of GitHub repositories, it can analyze and extract insights from its
own codebase and other codebases to improve its functionality. This
can lead to more efficient and effective code generation, better
semantic graph generation, and improved text generation capabilities.
I spent around 10 hours today on a major refactor creating a simple
pipeline abstraction and allowing dynamic instantiation from yaml
configs. It now also supports multiple GNN heads.
Please try it out and let me know what you think!
Example:
https://github.com/deepmind/clrs