Thats what I'am not quite sure about. I assume the result would not be close to the nash equilibrium.

But I don't know since I have not worked with transformers before.

I think it comes down to, can we train a transformer with feedback on what hands were good and which ones were not. Looking at other responses it seems like that is not possible.

But technically it should be possible to train the model on hands, in the mentioned representation, and get an output that would be a valid poker play?

I think the training part is what I was missing.

I thought you would train a transformer like a normal neural net in the sense that you tell it what output you like and what is wrong.

Looking into it a bit more I assume you could get an output but nothing close to the nash equilibrium.

Thank you for the feedback.