This is not an LLM obviously , it's just for generating random names. But interesting to think of the possibilities of truly tiny language models if there were connected together.
Hasn't it been repeatedly shown that many small models perform worse than a large model of the same total parameters?
LLMs are an imprecise, more of a marketing term, to define Transformer models based on the self-attention mechanism, trained with massives amounts of data.
And this implements a transformer. Actually it is a very cool didactic example.
Isn't a MoE model basically a cascading tree of smaller models or some variation of that?
It's an slm (small language model) due to number of parameters and it uses the same architecture as an llm, but llms have billions of parameters