🦣 MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning MathInstruct is a meticulously curated instruction tuning dataset that is lightweight yet generalizable. MathInstruct is compiled from 13 math rationale datasets, six of which are newly curated by this work. It uniquely focuses on the hybrid use of chain of thought (CoT) and program of thought (PoT) rationales, and ensures extensive coverage of diverse mathematical fields. Project Page: https://tiger ai lab.github.io/MAmmoTH/ Paper: https://arxiv.org/pdf/2309.05653.pdf Code: https://github.com/TIGER AI Lab/MAmmoTH Models: Base Model: Llama 2 Base Model: Code Llama 7B 🦣 MAmmoTH 7B 🦣 MAmmoTH Coder 7B 13B 🦣 MAmmoTH 13B 🦣 MAmmoTH Coder 13B 34B 🦣 MAmmoTH Coder 34B 70B 🦣 MAmmoTH 70B License Please check out the license of each subset in our curated dataset MathInstruct. Dataset Name License Type GSM8K MIT GSM8K RFT Non listed AQuA RAT Apache 2.0 MATH MIT TheoremQA MIT Camel Math Attribution NonCommercial 4.0 International NumGLUE Apache 2.0 MathQA Apache 2.0 Our Curated MIT Citation Please cite our paper if you use our data, model or code. Please also kindly cite the original dataset papers.
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