Llemma 7B is a language model for mathematics. It was initialized with Code Llama 7B weights, and trained on the Proof-Pile-2 for 200B tokens.
This model also comes in a 34B parameter version: Llemma 34B.
Evaluations
Llemma models are particularly strong at chain-of-thought mathematical reasoning and using computational tools for mathematics, such as Python and formal theorem provers.
Chain-of-thought Math
On chain-of-thought mathematics tasks, Llemma models outperform Llama-2, Code Llama, and when controlled for model size, outperform Minerva.
Further performance can be extracted by using majority voting:
Model
Size
GSM8k maj@100
OCW maj@100
MMLU-STEM maj@16
SAT maj@16
MATH maj@256
LLEMMA
7B
54.0%
14.3%
49.9%
78.1%
33.5
Minerva
8B
28.4%
12.5%
43.4%
-
25.4%
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LLEMMA
34B
69.3%
18.4%
59.7%
81.3%
43.1%
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Minerva
62B
68.5%
23.5%
63.5%
-
43.4%
Minerva
540B
78.5%
30.8%
75.0%
-
50.3%
Tool Use and Theorem Proving
In addition to chain-of-thought reasoning, Llemma has strong capabilities in computational mathematics tasks. For tool use and formal theorem proving evaluations, see our paper.
Citation
@misc{azerbayev2023llemma,
title={Llemma: An Open Language Model For Mathematics},
author={Zhangir Azerbayev and Hailey Schoelkopf and Keiran Paster and Marco Dos Santos and Stephen McAleer and Albert Q. Jiang and Jia Deng and Stella Biderman and Sean Welleck},
year={2023},
eprint={2310.10631},
archivePrefix={arXiv},
primaryClass={cs.CL}
}