The set.mm repo has a small set of Wiki pages.
I've been putting notes about automated proving, especially AI/ML, here:
https://github.com/metamath/set.mm/wiki/Automated-proving

I hope to someday work on AI/ML for creating Metamath proofs, but I haven't
had a chance to do it. I encourage anyone interested to give it a try, I think 
it's
*extremely* promising.

--- David A. Wheeler


> On Aug 19, 2023, at 8:32 PM, Amaury Hayat <[email protected]> wrote:
> 
> Hi Marcel,
> 
> There were actually several papers based on Transformers for Metamath. You 
> can probably check these two and the reference therein and it will give you a 
> good idea of what was done and what can be achieved (up to last year) :)
> 
> https://arxiv.org/abs/2009.03393
> 
> https://arxiv.org/abs/2205.11491
> 
> For transformers learning more or less complicated specific maths notions 
> (ODE, stability of ODEs, equilibrium in graphs, linear algebra, etc.) you can 
> check for instance https://arxiv.org/abs/1912.01412 (learning to solve ODEs), 
> https://arxiv.org/abs/2006.06462 (learning to predict advance properties such 
> as stability, controllability, etc.),  https://arxiv.org/abs/2112.03588 
> (learning to find equilibrium in graphs), https://arxiv.org/abs/2112.01898 
> (learning linear algebra). There are probably many other references but these 
> can give you a good start and their models and dataset are public.
> 
> Best,
> 
> 
> Le dim. 20 août 2023 à 06:30, 'Marcel Richter' via Metamath 
> <[email protected]> a écrit :
> I had a lot of fun training transformers on some toy data, and now i am 
> thinking what to do next. I was surprised how fast even small transformers 
> lern long multiplication. 
> 
> Anyone know if someone trained a GTP on set.mm yet.
> 
> set.mm is only ~40mb, i guess that is not enough to avoid overfitting really 
> fast. Anyone produced some procedural generated metamath code?
> 
> I belive a well trained model could be of great help as some kind of 
> methamath copilote.
> 
> Have a nice day :D
> 
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