appvoid

I guess the reason is slow is because llama.cpp is not optimized...

Correct! It's causal modeling (for now) with a char level tokenizer with only 8 tokens.

The model learns by looking for relationships of sequences for a single token, so the only way it learns is literally nudging weights towards a generalized solution using pure sequences.

In short, it learns to learn.

Will the be any app to.. convert the dots to something meaningful?

Not yet, I'm focusing on getting the core right first. But once the model is general enough, I don't see why not. Though you might need to finetune it for your use case.

Correct! It's causal modeling (for now) with a char level tokenizer with only 8 tokens.

The model learns by looking for relationships of sequences for a single token, so the only way it learns is literally nudging weights towards a generalized solution using pure sequences.

In short, it learns to learn.

The first model proudly trained from scratch on "physical" reasoning instead of chunky language tokens was published.

if you need raw power though slow, rwkv 0.4b has you covered, if you need something in between choose lfm2 350m