# Mathematical Problem Solving

MathFusionQA is a mathematical problem-solving model based on deepseek-math-7b-base, enhancing the mathematical problem-solving capabilities of large language models through instruction fusion.

This model is a reward model trained on the MathDial and MRBench datasets, specializing in mathematics education assistance and scaffolded learning.

Doge 160M Reasoning Distilled Version is a lightweight language model based on dynamic masked attention mechanism and cross-domain mixture of experts, focusing on reasoning and question-answering tasks.

Open Reasoner Zero is an open-source solution for large-scale reinforcement learning based on foundational models, focusing on scalability, simplicity, and ease of use for large-scale reasoning-oriented reinforcement learning.

OpenMath2-Llama3.1-70B is a specialized large language model for mathematics, fine-tuned using the OpenMathInstruct-2 dataset based on the Llama3.1-70B-Base model.

An optimized model based on Meta Llama 3, enhancing performance for multi-turn dialogue scenarios

HeroBophades-3x7B is an experimental Mixture of Experts (LLM) model built using mergekit, designed to run in 4-bit mode on GPUs with 12GB VRAM.

This model is constructed through expert collaboration methods, specializing in mathematical problem solving, capable of autonomously generating solutions or invoking GPT-4 level large models when necessary.

A 7B-parameter large language model based on the Mistral architecture, efficiently trained using Unsloth and TRL libraries, demonstrating excellent performance in multiple benchmarks.

TheProfessor is a hybrid model created by merging multiple pre-trained language models using the mergekit tool, specializing in conversational interaction, logical reasoning, scientific research, medical knowledge, and mathematical capabilities.

The LoftQ (LoRA Fine-tuning Aware Quantization) model provides a quantized backbone network and LoRA adapters, specifically designed for LoRA fine-tuning to improve the fine-tuning performance and efficiency of large language models during the quantization process.

MathOctopus is a multilingual mathematical reasoning large language model based on the LLaMA 2 architecture, supporting 10 languages and specializing in solving mathematical problems.

The MathCoder series of open-source large language models, specifically designed for general mathematical problem solving, fine-tuned based on Llama-2

The MathCoder series of open-source large language models, specifically tailored for general mathematical problem solving, fine-tuned based on Llama-2 and Code Llama.

MetaMath-Llemma-7B is a mathematical reasoning model fine-tuned on the MetaMathQA dataset, demonstrating excellent performance on GSM8K and MATH datasets.