Oct 16, 2023 · We present Llemma, a large language model for mathematics. We continue pretraining Code Llama on the Proof-Pile-2, a mixture of scientific papers, web data containing mathematics, and mathematical code, yielding Llemma.

Today we release Llemma: 7 billion and 34 billion parameter language models for mathematics. The Llemma models were initialized with Code Llama weights, then trained on the Proof-Pile II, a 55 billion token dataset of mathematical and scientific documents.

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.

Oct 16, 2023 · We present Llemma, a large language model for mathematics. We continue pretraining Code Llama on the Proof-Pile-2, a mixture of scientific papers, web data containing mathematics, and mathematical code, yielding Llemma.

Repository for Llemma: an open language model for mathematics [Azerbayev et al 2023]. This repository hosts data and training code related to the following artifacts: This repository also contains submodules related to the overlap, fine-tuning, and theorem proving experiments described in the paper.

a large language model for mathematics. We continue pretraining Code Llama on Proof-Pile-2, a mixture of scientific papers, web data containing mathematics. and mathematical code, yielding LLEMMA. On the MATH benchmark LLEMMA outperforms all known open base models, as well as the unreleased Minerv.

On the MATH benchmark Llemma outperforms all known open base models, as well as the unreleased Minerva model suite on an equi-parameter basis. Moreover, Llemma is capable of tool use and formal theorem proving without any further finetuning.

Oct 17, 2023 · Llemma 34B is a language model for mathematics. It was initialized with Code Llama 34B weights, and trained on the Proof-Pile-2 for 50B tokens. This model also comes in a 7B parameter version: Llemma 7B.

We observe a Ray error when running the 34b script (with VLLM --tp-degree > 1) on an untraced LeanDojo repo. A workaround is to run the 7b script with --tp-degree 1 such that LeanDojo completes tracing the repo. Then run the 34b script with --tp-degree > 1. Please cite the following: title={Llemma: An Open Language Model For Mathematics}, .

El término llema está escrito de forma incorrecta. La palabra escrita correctamente es yema con y.