University researchers and Eleuther AI introduce LLEMMA as an LLM for problems in mathematics. It is an open source model. It surpasses Google’s Minerva in performance.

It is based on code Llma, adopted after Facebook’s Llma 2 model duly fine-tuned. There are two versions of the model — one with 7 billion parameters and the other with 34 billion parameters. The models are fine-tuned on Proof-Pile-2, a set of scientific papers, web-data featuring maths and mathematical code.

LLEMMA is pre-trained on diverse maths data. It can use tools and can prove theorems without additional fine-tuning.

It can leverage Python interpreter and formal theorem provers to solve maths problems.

Google’s Minerva is not open source model. It is based on PaLM model.

This is a subject-specific model and not a general model.

Whether LLMs are suitable for problem solving is a matter of debate. Some scientists argue that LLMs are stochastic in nature and not suitable for math. Training data includes benchmark examples. There are efforts towards enhancing the reasoning and planning capabilities of language models. Maybe, they are not ultimate tools, but are the first step for further research for other types of models.